JMSLTM Numerical Library 7.2.0
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 

A

abs(Complex) - Static method in class com.imsl.math.Complex
Returns the absolute value (modulus) of a Complex, |z|.
abs(int) - Static method in class com.imsl.math.JMath
Returns the absolute value of an int.
abs(long) - Static method in class com.imsl.math.JMath
Returns the absolute value of a long.
abs(float) - Static method in class com.imsl.math.JMath
Returns the absolute value of a float.
abs(double) - Static method in class com.imsl.math.JMath
Returns the absolute value of a double.
ABS_CORRELATION_COEFFICIENT - Static variable in class com.imsl.stat.Dissimilarities
Indicates the absolute value of the correlation coefficient distance method.
ABS_COSINE - Static variable in class com.imsl.stat.Dissimilarities
Indicates the absolute value of the cosine of the angle between the vectors distance method.
ABS_DIFF - Static variable in class com.imsl.stat.TimeSeriesOperations.CombineMethod
Takes the absolute difference |ts1-ts2| between the two values.
absolute(int) - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the given row number in this ResultSet object.
AbstractChartNode - Class in com.imsl.chart
The base class of all of the nodes in both the 2D and 3D chart trees.
AbstractChartNode(AbstractChartNode) - Constructor for class com.imsl.chart.AbstractChartNode
 
AbstractFlatFile - Class in com.imsl.io
Reads a text or binary file as a ResultSet.
AbstractFlatFile() - Constructor for class com.imsl.io.AbstractFlatFile
Initializes an AbstractFlatFile.
AbstractFlatFile.FlatFileSQLException - Exception in com.imsl.io
A SQLException thrown by the AbstractFlatFile class.
AbstractFlatFile.FlatFileSQLFeatureNotSupportedException - Exception in com.imsl.io
A SQLFeatureNotSupportedException thrown by the AbstractFlatFile class.
accrint(GregorianCalendar, GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the interest which has accrued on a security that pays interest periodically.
accrintm(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the interest which has accrued on a security that pays interest at maturity.
ACCUMULATE - Static variable in class com.imsl.math.NumericalDerivatives
Indicates the accumulation of the result from whatever type of differences have been specified previously into initial values of the Jacobian.
acos(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse cosine (arc cosine) of a Complex, with branch cuts outside the interval [-1,1] along the real axis.
acos(double) - Static method in class com.imsl.math.JMath
Returns the inverse (arc) cosine of a double.
acosh(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse hyperbolic cosine (arc cosh) of a Complex, with a branch cut at values less than one along the real axis.
acosh(double) - Static method in class com.imsl.math.Hyperbolic
Returns the inverse hyperbolic cosine of its argument.
Activation - Interface in com.imsl.datamining.neural
Interface implemented by perceptron activation functions.
ADABOOST - Static variable in class com.imsl.datamining.GradientBoosting.LossFunctionType
The loss criteria is the AdaBoost.M1 criterion.
add(Complex, Complex) - Static method in class com.imsl.math.Complex
Returns the sum of two Complex objects, x+y.
add(Complex, double) - Static method in class com.imsl.math.Complex
Returns the sum of a Complex and a double, x+y.
add(double, Complex) - Static method in class com.imsl.math.Complex
Returns the sum of a double and a Complex, x+y.
add(Complex[][], Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Add two rectangular Complex arrays, a + b.
add(Complex, Complex, ComplexSparseMatrix, ComplexSparseMatrix) - Static method in class com.imsl.math.ComplexSparseMatrix
Performs element-wise addition of two complex sparse matrices A, B of type ComplexSparseMatrix, C leftarrow alpha A + beta B.
add(double[][], double[][]) - Static method in class com.imsl.math.Matrix
Add two rectangular arrays, a + b.
add(Physical, Physical) - Static method in class com.imsl.math.Physical
Add two compatible Physical objects.
add(double, double, SparseMatrix, SparseMatrix) - Static method in class com.imsl.math.SparseMatrix
Performs element-wise addition of two real sparse matrices A, B of type SparseMatrix, C leftarrow alpha A + beta B.
addCenterLine() - Method in class com.imsl.chart.qc.ShewhartControlChart
Adds the center line to the control chart and returns the newly added line.
addControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart
Adds a control limit to the chart.
addCumulativeLine(AxisXY) - Method in class com.imsl.chart.qc.ParetoChart
Adds a cumulative line to the specified axis.
addCumulativeLine() - Method in class com.imsl.chart.qc.ParetoChart
Creates a new right-side axis and adds a cumulative line to it.
addDataMarkers() - Method in class com.imsl.chart.qc.CuSumStatus
Adds the original data to the chart on a newly created axis.
addDataMarkers(AxisXY) - Method in class com.imsl.chart.qc.CuSumStatus
Adds the original data to the chart.
ADDITIVE - Static variable in class com.imsl.stat.ARMAOutlierIdentification
Indicates detection of an additive outlier.
ADDITIVE - Static variable in class com.imsl.stat.AutoARIMA
Indicates detection of an additive outlier.
addLegendItem(int, ChartNode) - Method in class com.imsl.chart.Chart
Adds a legend to this ChartNode.
addLowerControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart
Creates lower ControlLimit, adds it to the control chart, and returns the newly created object.
addMouseListener(MouseListener) - Method in class com.imsl.chart.Chart
Adds a MouseListener to the component associated with this chart.
addMouseMotionListener(MouseMotionListener) - Method in class com.imsl.chart.Chart
Adds a MouseMotionListener to the component associated with this chart.
addNode(Node) - Method in class com.imsl.datamining.neural.Layer
Associates a Perceptron with this Layer.
addPickListener(PickListener) - Method in class com.imsl.chart.ChartNode
Adds a PickListener to this node.
addPostRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart
Adds a Paint object to draw to the canvas after the the 3D image is rendered.
addPreRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart
Adds a Paint object to draw to the canvas before the the 3D image is rendered.
addSurrogates(Tree, double[]) - Method in class com.imsl.datamining.decisionTree.ALACART
Adds the surrogate information to the tree.
addSurrogates(Tree, double[]) - Method in interface com.imsl.datamining.decisionTree.DecisionTreeSurrogateMethod
Adds the surrogate information to the tree.
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AmbientLight
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Axis3D
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisBox
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisLabel
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisLine
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisTitle
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisXYZ
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Background
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Chart3D
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ChartLights
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ChartNode3D
Called to add this object to the scene graph.
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ColormapLegend
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Data
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.DirectionalLight
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.MajorTick
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.PointLight
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Surface
 
addUpperControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart
Creates upper ControlLimit, adds it to the control chart, and returns the newly created object.
addWecoLimits() - Method in class com.imsl.chart.qc.ShewhartControlChart
Adds lines for the Western Electric Company Rules.
ADJUSTED_R_SQUARED_CRITERION - Static variable in class com.imsl.stat.SelectionRegression
Indicates R^2_a (adjusted R^2) criterion regression.
AFTER_SUCCESSFUL_STEP - Static variable in class com.imsl.math.ODE
Used by method examineStep to indicate examining after a successful step
AFTER_UNSUCCESSFUL_STEP - Static variable in class com.imsl.math.ODE
Used by method examineStep to indicate examining after an unsuccessful step
afterLast() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the end of this ResultSet object, just after the last row.
aggregate() - Method in class com.imsl.datamining.BootstrapAggregation
Performs the bootstrap aggregation.
AIC - Static variable in class com.imsl.stat.AutoARIMA
Indicates that Akaike's information criterion (AIC) is used in the optimum model determination.
AICC - Static variable in class com.imsl.stat.AutoARIMA
Indicates that Akaike's corrected information criterion (AICC) is used in the optimum model determination.
ALACART - Class in com.imsl.datamining.decisionTree
Generates a decision tree using the CARTTM method of Breiman, Friedman, Olshen and Stone (1984).
ALACART(double[][], int, PredictiveModel.VariableType[]) - Constructor for class com.imsl.datamining.decisionTree.ALACART
Constructs an ALACART decision tree for a single response variable and multiple predictor variables.
ALL - Static variable in class com.imsl.stat.RegressorsForGLM
The n indicator variables are the dummy variables.
allConverged() - Method in class com.imsl.math.ZerosFunction
Returns true if the iterations for all of the roots have converged.
ALPHA_FACTOR_ANALYSIS - Static variable in class com.imsl.stat.FactorAnalysis
Indicates alpha factor analysis.
AmbientLight - Class in com.imsl.chart3d
An ambient light.
AmbientLight(Chart3D) - Constructor for class com.imsl.chart3d.AmbientLight
Creates an ambient light.
amordegrc(double, GregorianCalendar, GregorianCalendar, double, int, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the depreciation for each accounting period.
amorlinc(double, GregorianCalendar, GregorianCalendar, double, int, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the depreciation for each accounting period.
amultp(double[], double[]) - Method in interface com.imsl.math.ConjugateGradient.Function
A user-supplied function which computes z=Ap.
amultp(double[], double[]) - Method in interface com.imsl.math.GenMinRes.Function
Used to compute z = Ap where A is the matrix of coefficients to solve and p and z are arrays of length n, the order of matrix A.
ANCOVA - Class in com.imsl.stat
Analyzes a one-way classification model with covariates.
ANCOVA(double[][], double[][][]) - Constructor for class com.imsl.stat.ANCOVA
Constructs a one-way classification model with covariates.
ANGLE_IN_RADIANS - Static variable in class com.imsl.stat.Dissimilarities
Indicates the angle in radians (0, pi) between the lines through the origin defined by the vectors distance method.
Annotation - Class in com.imsl.chart
Draws an annotation.
Annotation(ChartNode, Text, double, double) - Constructor for class com.imsl.chart.Annotation
Creates a Text object at the specific x,y location in chart coordinates.
Annotation(ChartNode, String, double, double) - Constructor for class com.imsl.chart.Annotation
Draws a String at the specific x,y location in chart coordinates.
Annotation(ChartNode, Image, double, double) - Constructor for class com.imsl.chart.Annotation
Renders an Image object centered at an x,y location in chart coordinates.
ANNUAL - Static variable in class com.imsl.finance.Bond
Coupon payments are made annually.
ANOVA - Class in com.imsl.stat
Analysis of Variance table and related statistics.
ANOVA(double[][]) - Constructor for class com.imsl.stat.ANOVA
/** Analyzes a one-way classification model.
ANOVA(double, double, double, double, double) - Constructor for class com.imsl.stat.ANOVA
Construct an analysis of variance table and related statistics.
ANOVAFactorial - Class in com.imsl.stat
Analyzes a balanced factorial design with fixed effects.
ANOVAFactorial(int, int[], double[]) - Constructor for class com.imsl.stat.ANOVAFactorial
Constructor for ANOVAFactorial.
Apriori - Class in com.imsl.datamining
Performs the Apriori algorithm for association rule discovery.
AR_1 - Static variable in class com.imsl.stat.ARMAEstimateMissing
Indicates that missing values should be estimated using an autoregressive time series with 1 lag.
AR_P - Static variable in class com.imsl.stat.ARMAEstimateMissing
Indicates that missing values should be estimated using an autoregressive time series with a maximum lag of maxLag.
ARAutoUnivariate - Class in com.imsl.stat
Automatically determines the best autoregressive time series model using Akaike's Information Criterion.
ARAutoUnivariate(int, double[]) - Constructor for class com.imsl.stat.ARAutoUnivariate
ARAutoUnivariate constructor.
ARAutoUnivariate.TriangularMatrixSingularException - Exception in com.imsl.stat
The input triangular matrix is singular.
ARAutoUnivariate.TriangularMatrixSingularException(String) - Constructor for exception com.imsl.stat.ARAutoUnivariate.TriangularMatrixSingularException
Constructs a TriangularMatrixSingularException object.
ARAutoUnivariate.TriangularMatrixSingularException(String, Object[]) - Constructor for exception com.imsl.stat.ARAutoUnivariate.TriangularMatrixSingularException
Constructs a TriangularMatrixSingularException object.
argument(Complex) - Static method in class com.imsl.math.Complex
Returns the argument (phase) of a Complex, in radians, with a branch cut along the negative real axis.
ARMA - Class in com.imsl.stat
Computes least-square estimates of parameters for an ARMA model.
ARMA(int, int, double[]) - Constructor for class com.imsl.stat.ARMA
Constructor for ARMA.
ARMA.IllConditionedException - Exception in com.imsl.stat
The problem is ill-conditioned.
ARMA.IllConditionedException(String) - Constructor for exception com.imsl.stat.ARMA.IllConditionedException
Constructs an IllConditionedException with the specified detail message.
ARMA.IllConditionedException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.IllConditionedException
Constructs an IllConditionedException with the specified detail message.
ARMA.IncreaseErrRelException - Exception in com.imsl.stat
The bound for the relative error is too small.
ARMA.IncreaseErrRelException(String) - Constructor for exception com.imsl.stat.ARMA.IncreaseErrRelException
Constructs an IncreaseErrRelException with the specified detail message.
ARMA.IncreaseErrRelException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.IncreaseErrRelException
Constructs an IncreaseErrRelException with the specified detail message.
ARMA.MatrixSingularException - Exception in com.imsl.stat
The input matrix is singular.
ARMA.MatrixSingularException(String) - Constructor for exception com.imsl.stat.ARMA.MatrixSingularException
Constructs an MatrixSingularException with the specified detail message.
ARMA.MatrixSingularException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.MatrixSingularException
Constructs an MatrixSingularException with the specified detail message.
ARMA.NewInitialGuessException - Exception in com.imsl.stat
The iteration has not made good progress.
ARMA.NewInitialGuessException(String) - Constructor for exception com.imsl.stat.ARMA.NewInitialGuessException
Constructs an NewInitialGuessException with the specified detail message.
ARMA.NewInitialGuessException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.NewInitialGuessException
Constructs an NewInitialGuessException with the specified detail message.
ARMA.TooManyCallsException - Exception in com.imsl.stat
The number of calls to the function has exceeded the maximum number of iterations times the number of moving average (MA) parameters + 1.
ARMA.TooManyCallsException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyCallsException
Constructs an TooManyCallsException with the specified detail message.
ARMA.TooManyCallsException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyCallsException
Constructs an TooManyCallsException with the specified detail message.
ARMA.TooManyFcnEvalException - Exception in com.imsl.stat
Maximum number of function evaluations exceeded.
ARMA.TooManyFcnEvalException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyFcnEvalException
Constructs an TooManyFcnEvalException with the specified detail message.
ARMA.TooManyFcnEvalException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyFcnEvalException
Constructs an TooManyFcnEvalException with the specified detail message.
ARMA.TooManyITNException - Exception in com.imsl.stat
Maximum number of iterations exceeded.
ARMA.TooManyITNException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyITNException
Constructs an TooManyITNException with the specified detail message.
ARMA.TooManyITNException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyITNException
Constructs an TooManyITNException with the specified detail message.
ARMA.TooManyJacobianEvalException - Exception in com.imsl.stat
Maximum number of Jacobian evaluations exceeded.
ARMA.TooManyJacobianEvalException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyJacobianEvalException
Constructs an TooManyJacobianEvalException with the specified detail message.
ARMA.TooManyJacobianEvalException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyJacobianEvalException
Constructs an TooManyJacobianEvalException with the specified detail message.
ARMAEstimateMissing - Class in com.imsl.stat
Estimates missing values in a time series collected with equal spacing.
ARMAEstimateMissing(int[], double[]) - Constructor for class com.imsl.stat.ARMAEstimateMissing
Constructor for ARMAEstimateMissing.
ARMAMaxLikelihood - Class in com.imsl.stat
Computes maximum likelihood estimates of parameters for an ARMA model with p and q autoregressive and moving average terms respectively.
ARMAMaxLikelihood(int, int, double[]) - Constructor for class com.imsl.stat.ARMAMaxLikelihood
Constructor for ARMAMaxLikelihood.
ARMAMaxLikelihood.InitialMAException - Exception in com.imsl.stat
The initial values for the moving average parameters are not invertible.
ARMAMaxLikelihood.InitialMAException(String) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.InitialMAException
Constructs an InitialMAException with the specified detail message.
ARMAMaxLikelihood.InitialMAException(String, Object[]) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.InitialMAException
Constructs an InitialMAException with the specified detail message.
ARMAMaxLikelihood.NonInvertibleException - Exception in com.imsl.stat
The solution is noninvertible.
ARMAMaxLikelihood.NonInvertibleException(String) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonInvertibleException
Constructs a NonInvertible exception with the specified detail message.
ARMAMaxLikelihood.NonInvertibleException(String, Object[]) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonInvertibleException
Constructs a NonInvertibleException exception with the specified detail message.
ARMAMaxLikelihood.NonStationaryException - Exception in com.imsl.stat
The solution is nonstationary.
ARMAMaxLikelihood.NonStationaryException(String) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonStationaryException
Constructs a NonStationary exception with the specified detail message.
ARMAMaxLikelihood.NonStationaryException(String, Object[]) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonStationaryException
Constructs a NonStationary exception with the specified detail message.
ARMAOutlierIdentification - Class in com.imsl.stat
Detects and determines outliers and simultaneously estimates the model parameters in a time series whose underlying outlier free series follows a general seasonal or nonseasonal ARMA model.
ARMAOutlierIdentification(double[]) - Constructor for class com.imsl.stat.ARMAOutlierIdentification
Constructor for ARMAOutlierIdentification.
ARSeasonalFit - Class in com.imsl.stat
Estimates the optimum seasonality parameters for a time series using an autoregressive model, AR(p), to represent the time series.
ARSeasonalFit(int, int[][], double[]) - Constructor for class com.imsl.stat.ARSeasonalFit
Constructor for ARSeasonalFit.
ascending(int[]) - Static method in class com.imsl.stat.Sort
Sorts an integer array into ascending order.
ascending(int[], int[]) - Static method in class com.imsl.stat.Sort
Sorts an integer array into ascending order and returns the permutation vector.
ascending(double[]) - Static method in class com.imsl.stat.Sort
Sorts an array into ascending order.
ascending(double[], int[]) - Static method in class com.imsl.stat.Sort
Sorts an array into ascending order and returns the permutation vector.
ascending(double[][], int) - Static method in class com.imsl.stat.Sort
Sorts a matrix into ascending order by the first nKeys.
ascending(double[][], int[]) - Static method in class com.imsl.stat.Sort
Sorts a matrix into ascending order by specified keys.
ascending(double[][], int, int[]) - Static method in class com.imsl.stat.Sort
Sorts a matrix into ascending order according to the first nKeys keys and returns the permutation vector.
ascending(int[][], int) - Static method in class com.imsl.stat.Sort
Sorts a matrix into ascending order by the first nKeys.
ascending(int[][], int, int[]) - Static method in class com.imsl.stat.Sort
Sorts a matrix into ascending order according to the first nKeys keys and returns the permutation vector.
ascending(double[][], int[], int[]) - Static method in class com.imsl.stat.Sort
Sorts a matrix into ascending order by specified keys and returns the permutation vector.
ascending(int[][], int[], int[]) - Static method in class com.imsl.stat.Sort
Sorts a matrix into ascending order by specified keys and returns the permutation vector.
asin(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse sine (arc sine) of a Complex, with branch cuts outside the interval [-1,1] along the real axis.
asin(double) - Static method in class com.imsl.math.JMath
Returns the inverse (arc) sine of a double.
asinh(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse hyperbolic sine (arc sinh) of a Complex, with branch cuts outside the interval [-i,i].
asinh(double) - Static method in class com.imsl.math.Hyperbolic
Returns the inverse hyperbolic sine of its argument.
AssociationRule - Class in com.imsl.datamining
Association rule of the form X implies Y.
AT_BEGINNING_OF_PERIOD - Static variable in class com.imsl.finance.Finance
Flag used to indicate that payment is made at the beginning of each period.
AT_END_OF_PERIOD - Static variable in class com.imsl.finance.Finance
Flag used to indicate that payment is made at the end of each period.
atan(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse tangent (arc tangent) of a Complex, with branch cuts outside the interval [-i,i] along the imaginary axis.
atan(double) - Static method in class com.imsl.math.JMath
Returns the inverse (arc) tangent of a double.
atan2(double, double) - Static method in class com.imsl.math.JMath
Returns the angle corresponding to a Cartesian point.
atanh(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse hyperbolic tangent (arc tanh) of a Complex, with branch cuts outside the interval [-1,1] on the real axis.
atanh(double) - Static method in class com.imsl.math.Hyperbolic
Returns the inverse hyperbolic tangent of its argument.
AutoARIMA - Class in com.imsl.stat
Automatically identifies time series outliers, determines parameters of a multiplicative seasonal text{ARIMA}(p,0,q)times(0,d,0)_s model and produces forecasts that incorporate the effects of outliers whose effects persist beyond the end of the series.
AutoARIMA(int[], double[]) - Constructor for class com.imsl.stat.AutoARIMA
Constructor for AutoARIMA.
AutoARIMA.NoAcceptableModelFoundException - Exception in com.imsl.stat
No appropriate ARIMA model could be found.
AutoARIMA.NoAcceptableModelFoundException(String) - Constructor for exception com.imsl.stat.AutoARIMA.NoAcceptableModelFoundException
Constructs a NoAcceptableModelFoundException exception with the specified detail message.
AutoARIMA.NoAcceptableModelFoundException(String, Object[]) - Constructor for exception com.imsl.stat.AutoARIMA.NoAcceptableModelFoundException
Constructs a NoAcceptableModelFoundException exception with the specified detail message.
AutoCorrelation - Class in com.imsl.stat
Computes the sample autocorrelation function of a stationary time series.
AutoCorrelation(double[], int) - Constructor for class com.imsl.stat.AutoCorrelation
Constructor to compute the sample autocorrelation function of a stationary time series.
AutoCorrelation.NonPosVariancesException - Exception in com.imsl.stat
The problem is ill-conditioned.
AutoCorrelation.NonPosVariancesException(String) - Constructor for exception com.imsl.stat.AutoCorrelation.NonPosVariancesException
Constructs an NonPosVariancesException with the specified detail message.
AutoCorrelation.NonPosVariancesException(String, Object[]) - Constructor for exception com.imsl.stat.AutoCorrelation.NonPosVariancesException
Constructs an NonPosVariancesException with the specified detail message.
AUTOMATIC - Static variable in class com.imsl.chart.Treemap
Flag to set the treemap orientation automatically.
AUTOSCALE_DATA - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that autoscaling is to be done by scanning the data nodes.
AUTOSCALE_DENSITY - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that autoscaling is to adjust the "Density" attribute.
AUTOSCALE_NUMBER - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that autoscaling is to adjust the "Number" attribute.
AUTOSCALE_OFF - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that autoscaling is turned off.
AUTOSCALE_WINDOW - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that autoscaling is to be done by using the "Window" attribute.
AVERAGE - Static variable in class com.imsl.stat.TimeSeriesOperations.CombineMethod
Takes the average of the two values.
Axis - Class in com.imsl.chart
The Axis node provides the mapping for all of its children from the user coordinate space to the device (screen) space.
Axis(Chart) - Constructor for class com.imsl.chart.Axis
Contructs an Axis node.
Axis1D - Class in com.imsl.chart
An x-axis or a y-axis.
Axis3D - Class in com.imsl.chart3d
An x-axis, y-axis or a z-axis.
AXIS_TITLE_AT_END - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "AxisTitlePosition" indicating that the axis title should be placed at the end of the axis.
AXIS_TITLE_PARALLEL - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "AxisTitlePosition" indicating that the axis title should be placed parallel to the axis.
AXIS_X - Static variable in class com.imsl.chart.AbstractChartNode
Flag to indicate x-axis.
AXIS_X_TOP - Static variable in class com.imsl.chart.ChartNode
Flag to indicate x-axis placed on top of the chart.
AXIS_Y - Static variable in class com.imsl.chart.AbstractChartNode
Flag to indicate y-axis.
AXIS_Y_RIGHT - Static variable in class com.imsl.chart.ChartNode
Flag to indicate y-axis placed to the right of the chart.
AXIS_Z - Static variable in class com.imsl.chart.AbstractChartNode
Flag to indicate z-axis.
AxisBox - Class in com.imsl.chart3d
Box behind the axis.
AxisLabel - Class in com.imsl.chart
The labels on an axis.
AxisLabel - Class in com.imsl.chart3d
The labels on an axis.
AxisLine - Class in com.imsl.chart
The axis line.
AxisLine - Class in com.imsl.chart3d
The axis line.
AxisR - Class in com.imsl.chart
The R-axis in a polar plot.
AxisRLabel - Class in com.imsl.chart
The labels on an axis.
AxisRLine - Class in com.imsl.chart
The radius axis line in a polar plot.
AxisRMajorTick - Class in com.imsl.chart
The major tick marks for the radius axis in a polar plot.
AxisTheta - Class in com.imsl.chart
The angular axis in a polar plot.
AxisTitle - Class in com.imsl.chart
The title on an axis.
AxisTitle - Class in com.imsl.chart3d
Axis title.
AxisUnit - Class in com.imsl.chart
The unit title on an axis.
AxisXY - Class in com.imsl.chart
The axes for an x-y chart.
AxisXY(Chart) - Constructor for class com.imsl.chart.AxisXY
Create an AxisXY.
AxisXYZ - Class in com.imsl.chart3d
The axes for an x-y-z chart.
AxisXYZ(Chart3D) - Constructor for class com.imsl.chart3d.AxisXYZ
Create an AxisXYZ.

B

Background - Class in com.imsl.chart
The background of a chart.
Background - Class in com.imsl.chart3d
Background of the chart.
backshift(TimeSeries, int) - Method in class com.imsl.stat.TimeSeriesOperations
Returns the backshifted version of the time series.
backward(Complex[]) - Method in class com.imsl.math.ComplexFFT
Compute the complex periodic sequence from its Fourier coefficients.
backward(double[]) - Method in class com.imsl.math.FFT
Compute the real periodic sequence from its Fourier coefficients.
BACKWARD_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression
Indicates backward regression.
Bar - Class in com.imsl.chart
A bar chart.
Bar(AxisXY) - Constructor for class com.imsl.chart.Bar
Constructs a bar chart.
Bar(AxisXY, double[]) - Constructor for class com.imsl.chart.Bar
Constructs a simple bar chart using supplied y data.
Bar(AxisXY, double[], double[]) - Constructor for class com.imsl.chart.Bar
Constructs a simple bar chart using supplied x and y data.
Bar(AxisXY, double[][]) - Constructor for class com.imsl.chart.Bar
Constructs a grouped bar chart using supplied x and y data.
Bar(AxisXY, double[], double[][]) - Constructor for class com.imsl.chart.Bar
Constructs a grouped bar chart using supplied x and y data.
Bar(AxisXY, double[][][]) - Constructor for class com.imsl.chart.Bar
Constructs a stacked, grouped bar chart using supplied y data.
Bar(AxisXY, double[], double[][][]) - Constructor for class com.imsl.chart.Bar
Constructs a stacked, grouped bar chart using supplied x and y data.
BAR_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.ChartNode
Flag to indicate a horizontal bar chart.
BAR_TYPE_VERTICAL - Static variable in class com.imsl.chart.ChartNode
Flag to indicate a vertical bar chart.
BarItem - Class in com.imsl.chart
A single bar in a bar chart.
BarSet - Class in com.imsl.chart
A set of bars in a bar chart.
BARTLETTS_FORMULA - Static variable in class com.imsl.stat.AutoCorrelation
Indicates standard error computation using Bartlett's formula.
BARTLETTS_FORMULA - Static variable in class com.imsl.stat.CrossCorrelation
Indicates standard error computation using Bartlett's formula.
BARTLETTS_FORMULA_NOCC - Static variable in class com.imsl.stat.CrossCorrelation
Indicates standard error computation using Bartlett's formula with the assumption of no cross-correlation.
basis(int, double) - Method in interface com.imsl.stat.RegressionBasis
Public interface for the nonlinear least-squares function.
Basis30e360 - Static variable in class com.imsl.finance.DayCountBasis
Computations are based on the assumption of 30 days per month and 360 days per year.
BasisActual360 - Static variable in class com.imsl.finance.DayCountBasis
Computations are based on the number of days in a month based on the actual calendar value and the number of days, but assuming 360 days per year.
BasisActual365 - Static variable in class com.imsl.finance.DayCountBasis
Computations are based on the number of days in a month based on the actual calendar value and the number of days, but assuming 365 days per year.
BasisActualActual - Static variable in class com.imsl.finance.DayCountBasis
Computations are based on the actual calendar.
BasisNASD - Static variable in class com.imsl.finance.DayCountBasis
Computations are based on the assumption of 30 days per month and 360 days per year.
BasisPart - Interface in com.imsl.finance
Component of DayCountBasis.
BasisPart30E360 - Static variable in class com.imsl.finance.DayCountBasis
Computations are based on the assumption of 30 days per month and 360 days per year.
BasisPart365 - Static variable in class com.imsl.finance.DayCountBasis
Computations are based on the assumption of 365 days per year.
BasisPartActual - Static variable in class com.imsl.finance.DayCountBasis
Computations are are based on the actual calendar.
BasisPartNASD - Static variable in class com.imsl.finance.DayCountBasis
Computations based on the assumption of 30 days per month and 360 days per year.
BEFORE_STEP - Static variable in class com.imsl.math.ODE
Used by method examineStep to indicate examining before the next step
beforeFirst() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the front of this ResultSet object, just before the first row.
BEGIN_COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a column label is to be returned.
BEGIN_COLUMN_LABELS - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for beginning a column label row is to be returned.
BEGIN_ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatted string for beginning an entry is to be returned.
BEGIN_MATRIX - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for beginning a matrix is to be returned.
BEGIN_ROW - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for beginning a row is to be returned.
BEGIN_ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for beginning a row label is to be returned.
beginGet() - Method in class com.imsl.io.AbstractFlatFile
This method should be called at the start of every get Type method.
BERNOULLI - Static variable in class com.imsl.datamining.GradientBoosting.LossFunctionType
The loss criteria is the binomial or Bernoulli negative log-likelihood, or deviance.
Bessel - Class in com.imsl.math
Collection of Bessel functions.
beta(double, double) - Static method in class com.imsl.math.Sfun
Returns the value of the beta function.
beta(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the beta cumulative probability distribution function.
beta(double, double, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the beta cumulative probability distribution function.
beta(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the beta probability density function.
betaIncomplete(double, double, double) - Static method in class com.imsl.math.Sfun
Returns the incomplete beta function ratio.
betaMean(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the mean of the beta cumulative probability distribution function
BetaPD - Class in com.imsl.stat.distributions
The beta probability distribution
BetaPD() - Constructor for class com.imsl.stat.distributions.BetaPD
Constructor for the beta probability distribution
betaVariance(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the variance of the beta cumulative probability distribution function
BIC - Static variable in class com.imsl.stat.AutoARIMA
Indicates that the Bayesian information criterion (BIC) is used in the optimum model determination.
BIMONTHLY - Static variable in class com.imsl.finance.Bond
Coupon payments are made bimonthly (6 times per year).
BINARY_VARIABLE - Static variable in class com.imsl.io.MPSReader
Variable must be either 0 or 1.
BinaryClassification - Class in com.imsl.datamining.neural
Classifies patterns into two classes.
BinaryClassification(Network) - Constructor for class com.imsl.datamining.neural.BinaryClassification
Creates a binary classifier.
binomial(int, int, double) - Static method in class com.imsl.stat.Cdf
Evaluates the binomial cumulative probability distribution function.
binomial(int, int, double) - Static method in class com.imsl.stat.Pdf
Evaluates the binomial probability density function.
bivariateNormal(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the bivariate normal cumulative probability distribution function.
BLUE - Static variable in interface com.imsl.chart.Colormap
Linear blue colormap.
BLUE_GREEN_RED_YELLOW - Static variable in interface com.imsl.chart.Colormap
Blue/green/red/yellow colormap.
BLUE_RED - Static variable in interface com.imsl.chart.Colormap
Blue/red colormap.
BLUE_WHITE - Static variable in interface com.imsl.chart.Colormap
Blue/white colormap.
Bond - Class in com.imsl.finance
Collection of bond functions.
BONFERRONI - Static variable in class com.imsl.stat.ANOVA
The Bonferroni method
BootstrapAggregation - Class in com.imsl.datamining
Performs bootstrap aggregation to generate predictions using predictive models.
BootstrapAggregation(PredictiveModel) - Constructor for class com.imsl.datamining.BootstrapAggregation
Constructs a BootstrapAggregation class in order to generate predictions of a PredictiveModel using bootstrap aggregation.
BOUNDED_SCALING - Static variable in class com.imsl.datamining.neural.ScaleFilter
Flag to indicate bounded scaling.
BOUNDED_Z_SCORE_SCALING_MEAN_STDEV - Static variable in class com.imsl.datamining.neural.ScaleFilter
Flag to indicate bounded z-score scaling using the mean and standard deviation.
BOUNDED_Z_SCORE_SCALING_MEDIAN_MAD - Static variable in class com.imsl.datamining.neural.ScaleFilter
Flag to indicate bounded z-score scaling using the median and mean absolute difference.
BoundedLeastSquares - Class in com.imsl.math
Solves a nonlinear least-squares problem subject to bounds on the variables using a modified Levenberg-Marquardt algorithm.
BoundedLeastSquares(BoundedLeastSquares.Function, int, int, int, double[], double[]) - Constructor for class com.imsl.math.BoundedLeastSquares
Constructor for BoundedLeastSquares.
BoundedLeastSquares.FalseConvergenceException - Exception in com.imsl.math
False convergence - The iterates appear to be converging to a noncritical point.
BoundedLeastSquares.FalseConvergenceException(String) - Constructor for exception com.imsl.math.BoundedLeastSquares.FalseConvergenceException
Constructs an FalseConvergenceException with the specified detail message.
BoundedLeastSquares.FalseConvergenceException(String, Object[]) - Constructor for exception com.imsl.math.BoundedLeastSquares.FalseConvergenceException
Constructs an FalseConvergenceException with the specified detail message.
BoundedLeastSquares.Function - Interface in com.imsl.math
Public interface for the user-supplied function to evaluate the function that defines the least-squares problem.
BoundedLeastSquares.Jacobian - Interface in com.imsl.math
Public interface for the user-supplied function to compute the Jacobian.
BoundedVariableLeastSquares - Class in com.imsl.math
Solve a linear least-squares problem with bounds on the variables.
BoundedVariableLeastSquares(double[][], double[], double[], double[]) - Constructor for class com.imsl.math.BoundedVariableLeastSquares
Construct a new BoundedVariableLeastSquares instance to solve Ax-b subject to bounds on the variables.
BoundedVariableLeastSquares.TooManyIterException - Exception in com.imsl.math
Maximum number of iterations exceeded.
BoundedVariableLeastSquares.TooManyIterException(String) - Constructor for exception com.imsl.math.BoundedVariableLeastSquares.TooManyIterException
The maximum number of iterations has exceeded.
BoundedVariableLeastSquares.TooManyIterException(String, Object[]) - Constructor for exception com.imsl.math.BoundedVariableLeastSquares.TooManyIterException
The maximum number of iterations has exceeded.
BoxPlot - Class in com.imsl.chart
Draws a multiple-group Box plot.
BoxPlot(AxisXY, double[], double[][]) - Constructor for class com.imsl.chart.BoxPlot
Constructs a box plot chart node with specified x values.
BoxPlot(AxisXY, double[], BoxPlot.Statistics[]) - Constructor for class com.imsl.chart.BoxPlot
Constructs a box plot chart node with specified x values.
BoxPlot(AxisXY, double[][]) - Constructor for class com.imsl.chart.BoxPlot
Constructs a box plot chart.
BoxPlot.Statistics - Class in com.imsl.chart
Computes the statistics for one set of observations in a Boxplot.
BoxPlot.Statistics(double[]) - Constructor for class com.imsl.chart.BoxPlot.Statistics
Creates a new instance of BoxPlot.Statistics.
BOXPLOT_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.BoxPlot
Value for attribute "BoxPlotType" indicating that this is a horizontal box plot.
BOXPLOT_TYPE_VERTICAL - Static variable in class com.imsl.chart.BoxPlot
Value for attribute "BoxPlotType" indicating that this is a horizontal box plot.
breakPoint - Variable in class com.imsl.math.Spline
The breakpoint array of length n, where n is the number of piecewise polynomials.
BRESLOWS_APPROXIMATE - Static variable in class com.imsl.stat.ProportionalHazards
Breslows approximate method of handling ties.
BsInterpolate - Class in com.imsl.math
Extension of the BSpline class to interpolate data points.
BsInterpolate(double[], double[]) - Constructor for class com.imsl.math.BsInterpolate
Constructs a B-spline that interpolates the given data points.
BsInterpolate(double[], double[], int) - Constructor for class com.imsl.math.BsInterpolate
Constructs a B-spline that interpolates the given data points and order, using a default "not-a-knot" spline knot sequence.
BsInterpolate(double[], double[], int, double[]) - Constructor for class com.imsl.math.BsInterpolate
Constructs a B-spline that interpolates the given data points, using the specified order and knots.
BsLeastSquares - Class in com.imsl.math
Extension of the BSpline class to compute a least squares spline approximation to data points.
BsLeastSquares(double[], double[], int) - Constructor for class com.imsl.math.BsLeastSquares
Constructs a least squares B-spline approximation to the given data points.
BsLeastSquares(double[], double[], int, int) - Constructor for class com.imsl.math.BsLeastSquares
Constructs a least squares B-spline approximation to the given data points.
BsLeastSquares(double[], double[], int, int, double[], double[]) - Constructor for class com.imsl.math.BsLeastSquares
Constructs a least squares B-spline approximation to the given data points.
BSpline - Class in com.imsl.math
BSpline represents and evaluates univariate B-splines.
BSpline() - Constructor for class com.imsl.math.BSpline
 
BufferedPaint - Class in com.imsl.chart3d
A Paint object cached into an image.
BufferedPaint(Canvas3DChart.Paint, int, int, int, int, Component) - Constructor for class com.imsl.chart3d.BufferedPaint
The paint method in Canvas3DChart.Paint is written into an image of size width by height.
BW_LINEAR - Static variable in interface com.imsl.chart.Colormap
Black and white (grayscale) colormap.
byteValue() - Method in class com.imsl.math.Complex
Returns the value of the real part as a byte.

C

C45 - Class in com.imsl.datamining.decisionTree
Generates a decision tree using the C4.5 algorithm for a categorical response variable and categorical or quantitative predictor variables.
C45(double[][], int, PredictiveModel.VariableType[]) - Constructor for class com.imsl.datamining.decisionTree.C45
Constructs a C45 object for a single response variable and multiple predictor variables.
cancelRowUpdates() - Method in class com.imsl.io.AbstractFlatFile
Cancels the updates made to the current row in this ResultSet object.
Candlestick - Class in com.imsl.chart
Candlestick plot of stock data.
Candlestick(AxisXY, Date, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.Candlestick
Constructs a candlestick chart node beginning with specified start date.
Candlestick(AxisXY, double[], double[], double[], double[], double[]) - Constructor for class com.imsl.chart.Candlestick
Constructs a candlestick chart node at specified axis points.
CandlestickItem - Class in com.imsl.chart
A candlestick for the up days or the down days.
canonicalCorrelation(double[][]) - Method in class com.imsl.stat.Random
Method canonicalCorrelation generates a canonical correlation matrix from an arbitrarily distributed multivariate deviate sequence with nvar deviate variables, nseq steps in the sequence, and a Gaussian Copula dependence structure.
Canvas3DChart - Class in com.imsl.chart3d
A canvas for rendering a 3D chart.
Canvas3DChart() - Constructor for class com.imsl.chart3d.Canvas3DChart
Creates a Canvas3DChart with a new Chart3D object.
Canvas3DChart(Chart3D) - Constructor for class com.imsl.chart3d.Canvas3DChart
Creates a Canvas3DChart with a given Chart3D object.
Canvas3DChart.Paint - Interface in com.imsl.chart3d
Interface for 2D drawing on the canvas before or after the the 3D image is drawn.
capabilityIndexCp(double, double) - Method in class com.imsl.chart.qc.XbarR
Returns the capability index c_p

c_p=frac{mathrm{USL}-mathrm{LSL}}{6sigma}

capabilityIndexCp(double, double) - Method in class com.imsl.chart.qc.XbarS
Returns the capability index c_p

c_p=frac{mathrm{USL}-mathrm{LSL}}{6sigma}

capabilityIndexCpk(double, double) - Method in class com.imsl.chart.qc.XbarR
Returns the capability index c_{pk}

c_{pk}=minleft[frac{mathrm{USL}-bar{x}}{3sigma},frac{bar{x}-mathrm{LSL}}{3sigma}right]

capabilityIndexCpk(double, double) - Method in class com.imsl.chart.qc.XbarS
Returns the capability index c_{pk}

c_{pk}=minleft[frac{mathrm{USL}-bar{x}}{3sigma},frac{bar{x}-mathrm{LSL}}{3sigma}right]

CATEGORICAL - Static variable in class com.imsl.datamining.PredictiveModel.VariableType
The associated variable can take on one of a limited number of values (levels).
CategoricalGenLinModel - Class in com.imsl.stat
Analyzes categorical data using logistic, probit, Poisson, and other linear models.
CategoricalGenLinModel(double[][], int) - Constructor for class com.imsl.stat.CategoricalGenLinModel
Constructs a new CategoricalGenLinModel.
CategoricalGenLinModel.ClassificationVariableException - Exception in com.imsl.stat
The ClassificationVariable vector has not been initialized.
CategoricalGenLinModel.ClassificationVariableException() - Constructor for exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableException
Constructs a ClassificationVariableException.
CategoricalGenLinModel.ClassificationVariableLimitException - Exception in com.imsl.stat
The Classification Variable limit set by the user through setUpperBound has been exceeded.
CategoricalGenLinModel.ClassificationVariableLimitException(int) - Constructor for exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableLimitException
Constructs a ClassificationVariableLimitException.
CategoricalGenLinModel.ClassificationVariableValueException - Exception in com.imsl.stat
The number of distinct values for each Classification Variable must be greater than 1.
CategoricalGenLinModel.ClassificationVariableValueException(int, int) - Constructor for exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableValueException
Constructs a ClassificationVariableValueException.
CategoricalGenLinModel.DeleteObservationsException - Exception in com.imsl.stat
The number of observations to be deleted (set by setObservationMax) has grown too large.
CategoricalGenLinModel.DeleteObservationsException(int) - Constructor for exception com.imsl.stat.CategoricalGenLinModel.DeleteObservationsException
Constructs a DeleteObservationsException.
CategoricalGenLinModel.RankDeficientException - Exception in com.imsl.stat
The model has been determined to be rank deficient.
CategoricalGenLinModel.RankDeficientException(int) - Constructor for exception com.imsl.stat.CategoricalGenLinModel.RankDeficientException
Constructs a RankDeficientException.
CChart - Class in com.imsl.chart.qc
CChart is a c-chart for monitoring the count of the number of defects when defects are rare.
CChart(AxisXY, int[]) - Constructor for class com.imsl.chart.qc.CChart
Creates a C-chart given the number of defects in a series of samples.
Cdf - Class in com.imsl.stat
Cumulative probability distribution functions.
cdf(double) - Method in interface com.imsl.stat.CdfFunction
Public interface for the user-supplied cumulative distribution function to be used by InverseCdf.
CdfFunction - Interface in com.imsl.stat
Public interface for the user-supplied cumulative distribution function to be used by InverseCdf and ChiSquaredTest.
ceil(double) - Static method in class com.imsl.math.JMath
Returns the value of a double rounded toward positive infinity to an integral value.
CENTER_MEAN - Static variable in class com.imsl.stat.ARSeasonalFit
Indicates the transformed series should be centered using the average of the differenced series.
CENTER_MEDIAN - Static variable in class com.imsl.stat.ARSeasonalFit
Indicates the transformed series should be centered using the median of the differenced series.
CENTRAL - Static variable in class com.imsl.math.NumericalDerivatives
Indicates central differences.
CHAID - Class in com.imsl.datamining.decisionTree
Generates a decision tree using CHAID for categorical or discrete ordered predictor variables.
CHAID(double[][], int, PredictiveModel.VariableType[]) - Constructor for class com.imsl.datamining.decisionTree.CHAID
Constructs a CHAID object for a single response variable and multiple predictor variables.
Chart - Class in com.imsl.chart
The root node of the chart tree.
Chart() - Constructor for class com.imsl.chart.Chart
This is the root of our tree, it has no parent.
Chart(Component) - Constructor for class com.imsl.chart.Chart
This is the root of our tree, it has no parent.
Chart(Image) - Constructor for class com.imsl.chart.Chart
This is the root of our tree, it has no parent.
chart - Variable in class com.imsl.chart.JPanelChart
The embedded chart.
Chart3D - Class in com.imsl.chart3d
Root node of a 3d chart tree.
Chart3D() - Constructor for class com.imsl.chart3d.Chart3D
Creates a new instance of Chart3D
ChartFunction - Interface in com.imsl.chart
An interface that allows a function to be plotted.
ChartLights - Class in com.imsl.chart3d
Default set of lights.
ChartNode - Class in com.imsl.chart
The base class of all of the nodes in the 2D chart tree.
ChartNode(ChartNode) - Constructor for class com.imsl.chart.ChartNode
Construct a ChartNode object.
ChartNode3D - Class in com.imsl.chart3d
The base class of all of the nodes in the 3D chart tree.
ChartNode3D(ChartNode3D) - Constructor for class com.imsl.chart3d.ChartNode3D
Construct a ChartNode3D object.
ChartServlet - Class in com.imsl.chart
The base class for chart servlets.
ChartServlet() - Constructor for class com.imsl.chart.ChartServlet
 
ChartSpline - Class in com.imsl.chart
Wrap a spline into a ChartFunction to be plotted.
ChartSpline(Spline) - Constructor for class com.imsl.chart.ChartSpline
Creates a ChartSpline from a Spline.
ChartSpline(Spline, int) - Constructor for class com.imsl.chart.ChartSpline
Creates a ChartSpline from the derivative of a Spline.
ChartTitle - Class in com.imsl.chart
The main title of a chart.
ChartXML - Class in com.imsl.chart.xml
Create a Chart from an XML file.
ChartXML(String) - Constructor for class com.imsl.chart.xml.ChartXML
Creates a ChartXML from an XML file.
ChartXML(String, boolean) - Constructor for class com.imsl.chart.xml.ChartXML
Creates a ChartXML from an XML file.
ChartXML(InputSource, boolean) - Constructor for class com.imsl.chart.xml.ChartXML
Creates a ChartXML from an XML source.
ChartXML(Document) - Constructor for class com.imsl.chart.xml.ChartXML
Creates a ChartXML from a DOM tree.
check(int) - Method in class com.imsl.chart.Draw
 
checkCompatibility(Physical, Physical) - Static method in class com.imsl.math.Physical
Checks the compatibility of two Physical objects.
checkerboard(int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a checkerboard pattern.
checkMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Check that all of the rows in the Complex matrix have the same length.
checkMatrix(double[][]) - Static method in class com.imsl.math.Matrix
Check that all of the rows in the matrix have the same length.
checkSquareMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Check that the Complex matrix is square.
checkSquareMatrix() - Method in class com.imsl.math.ComplexSparseMatrix
Check that the matrix is square.
checkSquareMatrix(double[][]) - Static method in class com.imsl.math.Matrix
Check that the matrix is square.
checkSquareMatrix() - Method in class com.imsl.math.SparseMatrix
Check that the matrix is square.
chi(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the chi-squared cumulative distribution function.
chi(double, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the chi-squared cumulative probability distribution function.
chi(double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the chi-squared probability density function
chiMean(double) - Static method in class com.imsl.stat.Cdf
Evaluates the mean of the chi-squared cumulative probability distribution function
ChiSquaredTest - Class in com.imsl.stat
Chi-squared goodness-of-fit test.
ChiSquaredTest(CdfFunction, double[], int) - Constructor for class com.imsl.stat.ChiSquaredTest
Constructor for the Chi-squared goodness-of-fit test.
ChiSquaredTest(CdfFunction, int, int) - Constructor for class com.imsl.stat.ChiSquaredTest
Constructor for the Chi-squared goodness-of-fit test
ChiSquaredTest(int) - Method in class com.imsl.stat.NormalityTest
Performs the chi-squared goodness-of-fit test.
ChiSquaredTest.DidNotConvergeException - Exception in com.imsl.stat
The iteration did not converge
ChiSquaredTest.DidNotConvergeException(String) - Constructor for exception com.imsl.stat.ChiSquaredTest.DidNotConvergeException
Constructs a DidNotConvergeException object.
ChiSquaredTest.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.stat.ChiSquaredTest.DidNotConvergeException
Constructs a DidNotConvergeException object.
ChiSquaredTest.NoObservationsException - Exception in com.imsl.stat
There are no observations.
ChiSquaredTest.NoObservationsException(String, Object[]) - Constructor for exception com.imsl.stat.ChiSquaredTest.NoObservationsException
Constructs a NoObservationsException object.
ChiSquaredTest.NotCDFException - Exception in com.imsl.stat
The function is not a Cumulative Distribution Function (CDF).
ChiSquaredTest.NotCDFException(String, Object[]) - Constructor for exception com.imsl.stat.ChiSquaredTest.NotCDFException
Constructs a NotCDFException object.
chiVariance(double) - Static method in class com.imsl.stat.Cdf
Evaluates the variance of the chi-squared cumulative probability distribution function
Cholesky - Class in com.imsl.math
Cholesky factorization of a matrix of type double.
Cholesky(double[][]) - Constructor for class com.imsl.math.Cholesky
Create the Cholesky factorization of a symmetric positive definite matrix of type double.
Cholesky.NotSPDException - Exception in com.imsl.math
The matrix is not symmetric, positive definite.
Cholesky.NotSPDException() - Constructor for exception com.imsl.math.Cholesky.NotSPDException
Constructs a NotSPDException object.
circle(int, int, int) - Method in class com.imsl.chart.DrawMap
Sets a circle as the target.
classError(double[], int[], int) - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns the classification probability error for the input pattern and known target classification.
classify(double[], int) - Method in class com.imsl.stat.ClusterKNN
Classify an observation using k nearest neighbors.
classify(double[][], int) - Method in class com.imsl.stat.ClusterKNN
Classify a set of observations using k nearest neighbors.
classify(double[][]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations using the linear or quadratic discriminant functions generated during the training process.
classify(double[][], int[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations using the linear or quadratic discriminant functions generated during the training process.
classify(double[][], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations and associated frequencies and weights using the linear or quadratic discriminant functions generated during the training process.
classify(double[][], int[], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations and associated frequencies and weights using the linear or quadratic discriminant functions generated during the training process.
classify(double[][], int[], int[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations and compare against known groups using the linear or quadratic discriminant functions generated during the training process.
classify(double[][], int[], int[], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations, associated frequencies and weights, and compare against known groups using the linear or quadratic discriminant functions generated during the training process.
cleanup() - Method in class com.imsl.chart3d.Chart3D
Cleanup memory use and references used by the chart.
clearWarnings() - Method in class com.imsl.io.AbstractFlatFile
Clears all warnings reported on this ResultSet object.
clone(Map) - Method in class com.imsl.chart.AbstractChartNode
Returns a deep-copy clone of this node.
clone(Object, Map) - Method in class com.imsl.chart.AbstractChartNode
Returns a deep copy of an Object.
clone(Map, Map) - Method in class com.imsl.chart.AbstractChartNode
Returns a deep copy of a Hashtable.
clone(List, Map) - Method in class com.imsl.chart.AbstractChartNode
Returns a deep copy of a vector of ChartNode's.
clone() - Method in class com.imsl.chart.Chart
Returns a clone of the graphics tree.
clone(Map) - Method in class com.imsl.chart.Chart
Returns a clone of this node.
clone() - Method in class com.imsl.chart3d.BufferedPaint
 
clone() - Method in class com.imsl.chart3d.Chart3D
Returns a clone of the graphics tree.
clone(Map) - Method in class com.imsl.chart3d.Chart3D
Returns a clone of this node.
clone() - Method in class com.imsl.datamining.decisionTree.Tree
Returns a clone of this object.
clone() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns a clone of a TreeNode.
clone() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Clones a copy of the trainer.
clone() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Clones a copy of the trainer.
clone() - Method in class com.imsl.math.DenseLP
Creates and returns a copy of this object.
clone() - Method in class com.imsl.stat.FaureSequence
Returns a copy of this object.
clone() - Method in class com.imsl.stat.MersenneTwister
Returns a clone of this object.
clone() - Method in class com.imsl.stat.MersenneTwister64
Returns a clone of this object.
close() - Method in class com.imsl.io.AbstractFlatFile
Releases this ResultSet object's database and JDBC resources immediately instead of waiting for this to happen when it is automatically closed.
ClosedFormMaximumLikelihoodInterface - Interface in com.imsl.stat.distributions
A public interface for probability distributions that provide a method for a closed form solution of the maximum likelihood function
ClusterHierarchical - Class in com.imsl.stat
Performs a hierarchical cluster analysis from a distance matrix.
ClusterHierarchical(double[][]) - Constructor for class com.imsl.stat.ClusterHierarchical
Constructor for ClusterHierarchical.
ClusterKMeans - Class in com.imsl.stat
Perform a K-means (centroid) cluster analysis.
ClusterKMeans(double[][], double[][]) - Constructor for class com.imsl.stat.ClusterKMeans
Constructor for ClusterKMeans.
ClusterKMeans.ClusterNoPointsException - Exception in com.imsl.stat
There is a cluster with no points
ClusterKMeans.ClusterNoPointsException(String) - Constructor for exception com.imsl.stat.ClusterKMeans.ClusterNoPointsException
Constructs a ClusterNoPointsException object.
ClusterKMeans.ClusterNoPointsException(String, Object[]) - Constructor for exception com.imsl.stat.ClusterKMeans.ClusterNoPointsException
Constructs a ClusterNoPointsException object.
ClusterKMeans.NoConvergenceException - Exception in com.imsl.stat
Convergence did not occur within the maximum number of iterations.
ClusterKMeans.NoConvergenceException(String) - Constructor for exception com.imsl.stat.ClusterKMeans.NoConvergenceException
Constructs a NoConvergenceException object.
ClusterKMeans.NoConvergenceException(String, Object[]) - Constructor for exception com.imsl.stat.ClusterKMeans.NoConvergenceException
Constructs a NoConvergenceException object.
ClusterKNN - Class in com.imsl.stat
Perform a k-Nearest Neighbor classification.
ClusterKNN(double[][], int[]) - Constructor for class com.imsl.stat.ClusterKNN
Constructor for ClusterKNN.
coef - Variable in class com.imsl.math.BSpline
The B-spline coefficient array.
coef - Variable in class com.imsl.math.Spline
Coefficients of the piecewise polynomials.
color(double) - Method in interface com.imsl.chart.Colormap
Maps the parameterization interval [0,1] into Colors.
color(double, double, double) - Method in interface com.imsl.chart3d.ColorFunction
 
ColorFunction - Interface in com.imsl.chart3d
Interface to define value dependent colors.
Colormap - Interface in com.imsl.chart
Colormaps are mappings from the unit interval to Colors.
ColormapLegend - Class in com.imsl.chart3d
Adds a legend for a Colormap gradient to the background of the canvas.
ColormapLegend(Chart3D, Colormap, double[]) - Constructor for class com.imsl.chart3d.ColormapLegend
Creates a legend for a Colormap and adds it to the canvas.
ColormapLegend(Chart3D, Colormap, double, double) - Constructor for class com.imsl.chart3d.ColormapLegend
 
COLUMN_APPROXIMATE_MINIMUM_DEGREE - Static variable in class com.imsl.math.ComplexSuperLU
For column ordering, use column approximate minimum degree ordering.
COLUMN_APPROXIMATE_MINIMUM_DEGREE - Static variable in class com.imsl.math.SuperLU
For column ordering, use column approximate minimum degree ordering.
COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatted string for a given column label is to be returned.
COLUMN_SCALING - Static variable in class com.imsl.math.ComplexSuperLU
Indicates that input matrix A was column scaled before factorization.
COLUMN_SCALING - Static variable in class com.imsl.math.SuperLU
Indicates that input matrix A was column scaled before factorization.
COLUMNFIRST - Static variable in class com.imsl.chart.Treemap
Flag to set the treemap orientation drawing columns first.
com.imsl - package com.imsl
 
com.imsl.chart - package com.imsl.chart
 
com.imsl.chart.qc - package com.imsl.chart.qc
 
com.imsl.chart.xml - package com.imsl.chart.xml
 
com.imsl.chart3d - package com.imsl.chart3d
 
com.imsl.datamining - package com.imsl.datamining
 
com.imsl.datamining.decisionTree - package com.imsl.datamining.decisionTree
 
com.imsl.datamining.neural - package com.imsl.datamining.neural
 
com.imsl.finance - package com.imsl.finance
 
com.imsl.io - package com.imsl.io
 
com.imsl.math - package com.imsl.math
 
com.imsl.stat - package com.imsl.stat
 
com.imsl.stat.distributions - package com.imsl.stat.distributions
 
compareTo(Object) - Method in class com.imsl.math.Complex
Compares this Complex to another Object.
compareTo(Complex) - Method in class com.imsl.math.Complex
Compares two Complex objects.
complementaryChi(double, double) - Static method in class com.imsl.stat.Cdf
Calculates the complement of the chi-squared cumulative distribution function.
complementaryF(double, double, double) - Static method in class com.imsl.stat.Cdf
Calculates the complement of the F distribution function.
complementaryF2(double, double, double) - Static method in class com.imsl.stat.Cdf
 
complementaryNoncentralF(double, double, double, double) - Static method in class com.imsl.stat.Cdf
Calculates the complement of the noncentral F cumulative distribution function.
complementaryStudentsT(double, double) - Static method in class com.imsl.stat.Cdf
Calculates the complement of the Student's t distribution.
Complex - Class in com.imsl.math
Set of mathematical functions for complex numbers.
Complex(Complex) - Constructor for class com.imsl.math.Complex
Constructs a Complex equal to the argument.
Complex(double, double) - Constructor for class com.imsl.math.Complex
Constructs a Complex with real and imaginary parts given by the input arguments.
Complex(double) - Constructor for class com.imsl.math.Complex
Constructs a Complex with a zero imaginary part.
Complex() - Constructor for class com.imsl.math.Complex
Constructs a Complex equal to zero.
ComplexFFT - Class in com.imsl.math
Complex FFT.
ComplexFFT(int) - Constructor for class com.imsl.math.ComplexFFT
Constructs a complex FFT object.
ComplexLU - Class in com.imsl.math
LU factorization of a matrix of type Complex.
ComplexLU(Complex[][]) - Constructor for class com.imsl.math.ComplexLU
Creates the LU factorization of a square matrix of type Complex.
ComplexMatrix - Class in com.imsl.math
Complex matrix manipulation functions.
ComplexSparseCholesky - Class in com.imsl.math
Sparse Cholesky factorization of a matrix of type ComplexSparseMatrix.
ComplexSparseCholesky(ComplexSparseMatrix) - Constructor for class com.imsl.math.ComplexSparseCholesky
Constructs the matrix structure for the Cholesky factorization of a sparse Hermitian positive definite matrix of type ComplexSparseMatrix.
ComplexSparseCholesky.NotSPDException - Exception in com.imsl.math
The matrix is not Hermitian, positive definite.
ComplexSparseCholesky.NotSPDException() - Constructor for exception com.imsl.math.ComplexSparseCholesky.NotSPDException
Constructs a NotSPDException object.
ComplexSparseCholesky.NumericFactor - Class in com.imsl.math
Data structures and functions for the numeric Cholesky factor.
ComplexSparseCholesky.SymbolicFactor - Class in com.imsl.math
Data structures and functions for the symbolic Cholesky factor.
ComplexSparseMatrix - Class in com.imsl.math
Sparse matrix of type Complex.
ComplexSparseMatrix(int, int) - Constructor for class com.imsl.math.ComplexSparseMatrix
Creates a new instance of ComplexSparseMatrix.
ComplexSparseMatrix(ComplexSparseMatrix) - Constructor for class com.imsl.math.ComplexSparseMatrix
Creates a new instance of ComplexSparseMatrix which is a copy of another ComplexSparseMatrix.
ComplexSparseMatrix(ComplexSparseMatrix.SparseArray) - Constructor for class com.imsl.math.ComplexSparseMatrix
Constructs a complex sparse matrix from a SparseArray object.
ComplexSparseMatrix(int, int, int[][], Complex[][]) - Constructor for class com.imsl.math.ComplexSparseMatrix
Constructs a sparse matrix from SparseArray (Java Sparse Array) data.
ComplexSparseMatrix.SparseArray - Class in com.imsl.math
The SparseArray class uses public fields to hold the data for a sparse matrix in the Java Sparse Array format.
ComplexSparseMatrix.SparseArray() - Constructor for class com.imsl.math.ComplexSparseMatrix.SparseArray
 
ComplexSuperLU - Class in com.imsl.math
Computes the LU factorization of a general sparse matrix of type ComplexSparseMatrix by a column method and solves a sparse linear system of equations Ax=b.
ComplexSuperLU(ComplexSparseMatrix) - Constructor for class com.imsl.math.ComplexSuperLU
Constructor for ComplexSuperLU.
compute(double[], double[]) - Method in interface com.imsl.math.BoundedLeastSquares.Function
Public interface for the user-supplied function to evaluate the function that defines the least-squares problem.
compute(double[], double[]) - Method in interface com.imsl.math.BoundedLeastSquares.Jacobian
Public interface for the user-supplied function to compute the Jacobian.
compute() - Method in class com.imsl.math.CsTCB
Computes the tension-continuity-bias (TCB) cubic spline interpolant.
compute() - Method in class com.imsl.math.Spline2DLeastSquares
Computes a two-dimensional, tensor-product spline approximant using least squares.
compute() - Method in class com.imsl.stat.ANCOVA
Performs one-way analysis of covariance assuming parallelism and returns an array containing the parallelism tests for the one-way analysis of covariance.
compute() - Method in class com.imsl.stat.ANOVAFactorial
Analyzes a balanced factorial design with fixed effects.
compute() - Method in class com.imsl.stat.ARAutoUnivariate
Determines the autoregressive model with the minimum AIC by fitting autoregressive models from 0 to maxlag lags using the method of moments or an estimation method specified by the user through setEstimationMethod.
compute() - Method in class com.imsl.stat.ARMA
Computes least-square estimates of parameters for an ARMA model.
compute() - Method in class com.imsl.stat.ARMAMaxLikelihood
Computes the exact maximum likelihood estimates for the autoregressive and moving average parameters of an ARMA time series
compute(int[]) - Method in class com.imsl.stat.ARMAOutlierIdentification
Detects and determines outliers and simultaneously estimates the model parameters for the given time series.
compute() - Method in class com.imsl.stat.ARSeasonalFit
Computes the minimum AIC and optimum values for s and d based upon the candidates provided in sInitial and dInitial, and computes the values for the transformed series, W_t(s,d).
compute(int) - Method in class com.imsl.stat.AutoARIMA
Estimates potential missing values, detects and determines outliers and simultaneously fits an optimum model from a set of different text{ARIMA}(p,0,0)times(0,d,0)_s models to the outlier free time series.
compute(int[], int[]) - Method in class com.imsl.stat.AutoARIMA
Estimates potential missing values, detects and determines outliers and simultaneously fits an optimum model from a set of different text{ARIMA}(p,0,q)times(0,d,0)_s models to the outlier free time series.
compute(int, int, int, int) - Method in class com.imsl.stat.AutoARIMA
Estimates potential missing values, detects and determines outliers and simultaneously fits an text{ARIMA}(p,0,q)times(0,d,0)_s model to the outlier free time series.
compute() - Method in class com.imsl.stat.ClusterHierarchical
Performs a hierarchical cluster analysis.
compute() - Method in class com.imsl.stat.ClusterKMeans
Computes the cluster means.
compute(int) - Method in class com.imsl.stat.Covariances
Computes the matrix.
compute(double[], int[]) - Method in class com.imsl.stat.Difference
Computes a Difference series.
compute() - Method in class com.imsl.stat.Dissimilarities
Computes a matrix of dissimilarities (or similarities) between the columns (or rows) of a matrix.
compute() - Method in class com.imsl.stat.distributions.MaximumLikelihoodEstimation
Computes the maximum likelihood estimates.
compute() - Method in class com.imsl.stat.GARCH
Computes estimates of the parameters of a GARCH(p,q) model.
compute() - Method in class com.imsl.stat.HoltWintersExponentialSmoothing
Computes the values of the smoothing parameters.
compute(int, double[], int, int) - Static method in class com.imsl.stat.LackOfFit
Performs lack-of-fit test for a univariate time series or transfer function given the appropriate correlation function using a minimum lag of 1.
compute(int, double[], int, int, int) - Static method in class com.imsl.stat.LackOfFit
Performs lack-of-fit test for a univariate time series or transfer function given the appropriate correlation function.
compute() - Method in class com.imsl.stat.MultipleComparisons
Performs Student-Newman-Keuls multiple comparisons test.
compute(double[][], double[]) - Method in class com.imsl.stat.SelectionRegression
Computes the best multiple linear regression models.
compute(double[][], double[], double[]) - Method in class com.imsl.stat.SelectionRegression
Computes the best weighted multiple linear regression models.
compute(double[][], double[], double[], double[]) - Method in class com.imsl.stat.SelectionRegression
Computes the best weighted multiple linear regression models using frequencies for each observation.
compute(double[][], int) - Method in class com.imsl.stat.SelectionRegression
Computes the best multiple linear regression models using a user-supplied covariance matrix.
compute() - Method in class com.imsl.stat.SignTest
Performs a sign test.
compute() - Method in class com.imsl.stat.StepwiseRegression
Builds the multiple linear regression models using forward selection, backward selection, or stepwise selection.
compute(double, double) - Method in interface com.imsl.stat.TimeSeriesOperations.Function
Public interface for the user-supplied function to combine two time series values that occur at the same date and time.
compute() - Method in class com.imsl.stat.WilcoxonRankSum
Performs a Wilcoxon rank sum test using an approximate p-value calculation.
computeCoefficients(int, int, FeynmanKac.Boundaries, double[], double[]) - Method in class com.imsl.math.FeynmanKac
Determines the coefficients of the Hermite quintic splines that represent an approximate solution for the Feynman-Kac PDE.
computeExactPValues() - Method in class com.imsl.stat.WilcoxonRankSum
Performs a Wilcoxon rank sum test using exact p-value calculations.
computeForecasts(int) - Method in class com.imsl.stat.ARMAOutlierIdentification
Computes forecasts, associated probability limits and psi weights for an outlier contaminated time series whose underlying outlier free series obeys a general seasonal or non-seasonal ARMA model.
computeLags(int[], int[], double[]) - Method in class com.imsl.datamining.neural.TimeSeriesClassFilter
Computes lags of an array sorted first by class designations and then descending chronological order.
computeLags(int, double[][]) - Method in class com.imsl.datamining.neural.TimeSeriesFilter
Lags time series data to a format used for input to a neural network.
computeMin(MinUncon.Function) - Method in class com.imsl.math.MinUncon
Return the minimum of a smooth function of a single variable of type double using function values only or using function values and derivatives.
computeMin(MinUnconMultiVar.Function) - Method in class com.imsl.math.MinUnconMultiVar
Return the minimum point of a function of n variables of type double using a finite-difference gradient or using a user-supplied gradient.
computeRoots(double[]) - Method in class com.imsl.math.ZeroPolynomial
Computes the roots of the polynomial with real coefficients.
computeRoots(Complex[]) - Method in class com.imsl.math.ZeroPolynomial
Computes the roots of the polynomial with Complex coefficients.
computeStatistics(double[][], int[]) - Method in class com.imsl.datamining.neural.BinaryClassification
Computes the classification error statistics for the supplied network patterns and their associated classifications.
computeStatistics(double[][], int[]) - Method in class com.imsl.datamining.neural.MultiClassification
Computes classification statistics for the supplied network patterns and their associated classifications.
computeStatistics(double[][], double[][]) - Method in class com.imsl.datamining.neural.Network
Computes error statistics.
computeZeros(ZerosFunction.Function) - Method in class com.imsl.math.ZerosFunction
Returns the zeros of a univariate function.
condition(Complex[][]) - Method in class com.imsl.math.ComplexLU
Return an estimate of the reciprocal of the L_1 condition number.
condition(double[][]) - Method in class com.imsl.math.LU
Return an estimate of the reciprocal of the L_1 condition number of a matrix.
confidenceMean(double) - Method in class com.imsl.stat.Summary
Returns the confidence interval for the mean (assuming normality).
confidenceVariance(double) - Method in class com.imsl.stat.Summary
Returns the confidence interval for the variance (assuming normality).
conjugate(Complex) - Static method in class com.imsl.math.Complex
Returns the complex conjugate of a Complex object.
ConjugateGradient - Class in com.imsl.math
Solves a real symmetric definite linear system using the conjugate gradient method with optional preconditioning.
ConjugateGradient(int, ConjugateGradient.Function) - Constructor for class com.imsl.math.ConjugateGradient
Conjugate gradient constructor.
ConjugateGradient.Function - Interface in com.imsl.math
Public interface for the user supplied function to ConjugateGradient.
ConjugateGradient.NoConvergenceException - Exception in com.imsl.math
The conjugate gradient method did not converge within the allowed maximum number of iterations.
ConjugateGradient.NoConvergenceException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NoConvergenceException
Constructs a NoConvergenceException object.
ConjugateGradient.NoConvergenceException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NoConvergenceException
Constructs a NoConvergenceException object.
ConjugateGradient.NotDefiniteAMatrixException - Exception in com.imsl.math
The input matrix A is indefinite, that is the matrix is not positive or negative definite.
ConjugateGradient.NotDefiniteAMatrixException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteAMatrixException
Constructs a NotDefiniteAMatrixException object.
ConjugateGradient.NotDefiniteAMatrixException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteAMatrixException
Constructs a NotDefiniteAMatrixException object.
ConjugateGradient.NotDefiniteJacobiPreconditionerException - Exception in com.imsl.math
The Jacobi preconditioner is not strictly positive or negative definite.
ConjugateGradient.NotDefiniteJacobiPreconditionerException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteJacobiPreconditionerException
Constructs a NotDefiniteJacobiPreconditionerException object.
ConjugateGradient.NotDefiniteJacobiPreconditionerException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteJacobiPreconditionerException
Constructs a NotDefiniteJacobiPreconditionerException object.
ConjugateGradient.NotDefinitePreconditionMatrixException - Exception in com.imsl.math
The Precondition matrix is indefinite.
ConjugateGradient.NotDefinitePreconditionMatrixException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefinitePreconditionMatrixException
Constructs a NotDefinitePreconditionMatrixException object.
ConjugateGradient.NotDefinitePreconditionMatrixException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefinitePreconditionMatrixException
Constructs a NotDefinitePreconditionMatrixException object.
ConjugateGradient.Preconditioner - Interface in com.imsl.math
Public interface for the user supplied function to ConjugateGradient used for preconditioning.
ConjugateGradient.SingularPreconditionMatrixException - Exception in com.imsl.math
The Precondition matrix is singular.
ConjugateGradient.SingularPreconditionMatrixException(String) - Constructor for exception com.imsl.math.ConjugateGradient.SingularPreconditionMatrixException
Constructs a SingularPreconditionMatrixException object.
ConjugateGradient.SingularPreconditionMatrixException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.SingularPreconditionMatrixException
Constructs a SingularPreconditionMatrixException object.
conjugateTranspose() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the conjugate transpose of the matrix.
constant(String) - Static method in class com.imsl.math.Physical
Returns the value of a constant, given its name.
constant(String, String) - Static method in class com.imsl.math.Physical
Returns the value of a constant, given its name, in the specified units.
ContingencyTable - Class in com.imsl.stat
Performs a chi-squared analysis of a two-way contingency table.
ContingencyTable(double[][]) - Constructor for class com.imsl.stat.ContingencyTable
Constructs and performs a chi-squared analysis of a two-way contingency table.
CONTINUOUS_VARIABLE - Static variable in class com.imsl.io.MPSReader
Variable is a real number.
Contour - Class in com.imsl.chart
A Contour chart shows level curves of a two-dimensional function.
Contour(AxisXY, double[], double[], double[][], double[]) - Constructor for class com.imsl.chart.Contour
Create a Contour chart from rectangularly gridded data.
Contour(AxisXY, double[], double[], double[][]) - Constructor for class com.imsl.chart.Contour
Create a Contour chart from rectangularly gridded data with computed contour levels.
Contour(AxisXY, double[], double[], double[]) - Constructor for class com.imsl.chart.Contour
Create a Contour chart from scattered data with computed contour levels.
Contour(AxisXY, double[], double[], double[], double[], int) - Constructor for class com.imsl.chart.Contour
Create a Contour chart from scattered data.
Contour.Legend - Class in com.imsl.chart
A legend for a contour chart.
ContourLevel - Class in com.imsl.chart
ContourLevel draws a level curve line and the fill area between the level curve and the next smaller level curve.
ControlLimit - Class in com.imsl.chart.qc
ControlLimit is a control limit line on a process control chart.
convert(Physical, String) - Static method in class com.imsl.math.Physical
Converts a value to a different set of units.
convexity(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the convexity for a security.
copy() - Method in class com.imsl.chart.Chart
Copy the chart to the clipboard.
copyAndSortData(double[], double[]) - Method in class com.imsl.math.Spline
Copy and sort xData into breakPoint and yData into the first column of coef.
copyAndSortData(double[], double[], double[]) - Method in class com.imsl.math.Spline
Copy and sort xData into breakPoint and yData into the first column of coef.
copysign(double, double) - Static method in class com.imsl.math.IEEE
Returns a value with the magnitude of x and with the sign bit of y.
CORRECTED_SSCP_MATRIX - Static variable in class com.imsl.stat.Covariances
Indicates corrected sums of squares and crossproducts matrix.
CORRELATION_COEFFICIENT - Static variable in class com.imsl.stat.Dissimilarities
Indicates the correlation coefficient distance method.
CORRELATION_MATRIX - Static variable in class com.imsl.stat.Covariances
Indicates correlation matrix.
CORRELATION_MATRIX - Static variable in class com.imsl.stat.FactorAnalysis
Indicates correlation matrix.
cos(Complex) - Static method in class com.imsl.math.Complex
Returns the cosine of a Complex.
cos(double) - Static method in class com.imsl.math.JMath
Returns the cosine of a double.
cosh(Complex) - Static method in class com.imsl.math.Complex
Returns the hyperbolic cosh of a Complex.
cosh(double) - Static method in class com.imsl.math.Hyperbolic
Returns the hyperbolic cosine of its argument.
cot(double) - Static method in class com.imsl.math.Sfun
Returns the cotangent of a double.
countFrequency(Itemsets, int[][]) - Static method in class com.imsl.datamining.Apriori
Returns the frequency of each itemset in the transaction data set, x.
countFrequency(Itemsets, int[][], int[]) - Static method in class com.imsl.datamining.Apriori
Returns the frequency of each itemset in the transaction data set, x, added to the previous frequencies.
countTokens() - Method in class com.imsl.io.Tokenizer
Returns the number of times that the nextToken method can be called without generating an exception.
coupdaybs(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the number of days starting with the beginning of the coupon period and ending with the settlement date.
coupdays(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the number of days in the coupon period containing the settlement date.
coupdaysnc(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the number of days starting with the settlement date and ending with the next coupon date.
coupncd(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the first coupon date which follows the settlement date.
coupnum(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the number of coupons payable between the settlement date and the maturity date.
couppcd(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the coupon date which immediately precedes the settlement date.
Covariances - Class in com.imsl.stat
Computes the sample variance-covariance or correlation matrix.
Covariances(double[][]) - Constructor for class com.imsl.stat.Covariances
Constructor for Covariances.
Covariances.NonnegativeFreqException - Exception in com.imsl.stat
Frequencies must be nonnegative.
Covariances.NonnegativeFreqException(String) - Constructor for exception com.imsl.stat.Covariances.NonnegativeFreqException
Constructs a NonnegativeFreqException object.
Covariances.NonnegativeFreqException(String, Object[]) - Constructor for exception com.imsl.stat.Covariances.NonnegativeFreqException
Constructs a NonnegativeFreqException object.
Covariances.NonnegativeWeightException - Exception in com.imsl.stat
Weights must be nonnegative.
Covariances.NonnegativeWeightException(String) - Constructor for exception com.imsl.stat.Covariances.NonnegativeWeightException
Constructs a NonnegativeWeightException object.
Covariances.NonnegativeWeightException(String, Object[]) - Constructor for exception com.imsl.stat.Covariances.NonnegativeWeightException
Constructs a NonnegativeWeightException object.
createCharts(Chart, double[][]) - Static method in class com.imsl.chart.qc.XbarR
Creates a combined XbarR chart and RChart from data.
createCharts(Chart, int, double[], double[]) - Static method in class com.imsl.chart.qc.XbarR
Creates a combined XbarR chart and RChart given the means and ranges for a series of equally sized samples.
createCharts(Chart, int[], double[], double[]) - Static method in class com.imsl.chart.qc.XbarR
Creates a combined XbarR chart and RChart given the means and ranges for a series of unequally sized samples.
createCharts(Chart, double[][]) - Static method in class com.imsl.chart.qc.XbarS
Creates a combined XbarS chart and SChart from data.
createCharts(Chart, int, double[], double[]) - Static method in class com.imsl.chart.qc.XbarS
Creates a combined XbarS chart and SChart given the means and in sample standard deviations for a series of equally sized samples.
createCharts(Chart, int[], double[], double[]) - Static method in class com.imsl.chart.qc.XbarS
Creates a combined X-bar chart and S-chart given the means and in sample standard deviations for a series of unequally sized samples.
createContinuousAttribute(ProbabilityDistribution) - Method in class com.imsl.datamining.NaiveBayesClassifier
Create a continuous variable and the associated distribution function.
createContinuousAttribute(ProbabilityDistribution[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Create a continuous variable and the associated distribution functions for each target classification.
createCumulativeLineAxis() - Method in class com.imsl.chart.qc.ParetoChart
Creates a new axis to hold a cumulative line.
createCustomMarker() - Method in interface com.imsl.chart3d.Data.CustomMarkerFactory
Returns a custom marker.
createDataAxis() - Method in class com.imsl.chart.qc.CuSumStatus
Creates a new axis to hold a cummulative line.
createHiddenLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Creates a HiddenLayer.
createHiddenLayer() - Method in class com.imsl.datamining.neural.Network
Creates the next HiddenLayer in the Network.
createInput() - Method in class com.imsl.datamining.neural.InputLayer
Creates an InputNode in the InputLayer of the neural network.
createInputs(int) - Method in class com.imsl.datamining.neural.InputLayer
Creates a number of InputNodes in this Layer of the neural network.
createNominalAttribute(int) - Method in class com.imsl.datamining.NaiveBayesClassifier
Create a nominal attribute and the number of categories
createPerceptron(Activation, double) - Method in class com.imsl.datamining.neural.HiddenLayer
Creates a Perceptron in this Layer with a specified activation function and bias.
createPerceptron() - Method in class com.imsl.datamining.neural.HiddenLayer
Creates a Perceptron in this Layer of the neural network.
createPerceptron(Activation, double) - Method in class com.imsl.datamining.neural.OutputLayer
Creates a Perceptron in this Layer with a specified Activation and bias.
createPerceptron() - Method in class com.imsl.datamining.neural.OutputLayer
Creates a Perceptron in this Layer of the neural network.
createPerceptrons(int) - Method in class com.imsl.datamining.neural.HiddenLayer
Creates a number of Perceptrons in this Layer of the neural network.
createPerceptrons(int, Activation, double) - Method in class com.imsl.datamining.neural.HiddenLayer
Creates a number of Perceptrons in this Layer with the specified bias.
createPerceptrons(int) - Method in class com.imsl.datamining.neural.OutputLayer
Creates a number of Perceptrons in this Layer of the neural network.
createPerceptrons(int, Activation, double) - Method in class com.imsl.datamining.neural.OutputLayer
Creates a number of Perceptrons in this Layer with specified activation and bias.
CrossCorrelation - Class in com.imsl.stat
Computes the sample cross-correlation function of two stationary time series.
CrossCorrelation(double[], double[], int) - Constructor for class com.imsl.stat.CrossCorrelation
Constructor to compute the sample cross-correlation function of two stationary time series.
CrossCorrelation.NonPosVariancesException - Exception in com.imsl.stat
The problem is ill-conditioned.
CrossCorrelation.NonPosVariancesException(String) - Constructor for exception com.imsl.stat.CrossCorrelation.NonPosVariancesException
Constructs a NonPosVariancesException object.
CrossCorrelation.NonPosVariancesException(String, Object[]) - Constructor for exception com.imsl.stat.CrossCorrelation.NonPosVariancesException
Constructs a NonPosVariancesException object.
crosshatch(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a horizonal and vertical crosshatch pattern.
crossValidate() - Method in class com.imsl.datamining.CrossValidation
Performs V-Fold cross-validation.
CrossValidation - Class in com.imsl.datamining
Performs V-Fold cross-validation for predictive models.
CrossValidation(PredictiveModel) - Constructor for class com.imsl.datamining.CrossValidation
Creates a CrossValidation object.
CsAkima - Class in com.imsl.math
Extension of the Spline class to handle the Akima cubic spline.
CsAkima(double[], double[]) - Constructor for class com.imsl.math.CsAkima
Constructs the Akima cubic spline interpolant to the given data points.
CsInterpolate - Class in com.imsl.math
Extension of the Spline class to interpolate data points.
CsInterpolate(double[], double[]) - Constructor for class com.imsl.math.CsInterpolate
Constructs a cubic spline that interpolates the given data points.
CsInterpolate(double[], double[], int, double, int, double) - Constructor for class com.imsl.math.CsInterpolate
Constructs a cubic spline that interpolates the given data points with specified derivative endpoint conditions.
CsPeriodic - Class in com.imsl.math
Extension of the Spline class to interpolate data points with periodic boundary conditions.
CsPeriodic(double[], double[]) - Constructor for class com.imsl.math.CsPeriodic
Constructs a cubic spline that interpolates the given data points with periodic boundary conditions.
CsShape - Class in com.imsl.math
Extension of the Spline class to interpolate data points consistent with the concavity of the data.
CsShape(double[], double[]) - Constructor for class com.imsl.math.CsShape
Construct a cubic spline interpolant which is consistent with the concavity of the data.
CsShape.TooManyIterationsException - Exception in com.imsl.math
Too many iterations.
CsShape.TooManyIterationsException() - Constructor for exception com.imsl.math.CsShape.TooManyIterationsException
Constructs a TooManyIterationsException object.
CsShape.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.math.CsShape.TooManyIterationsException
Constructs a TooManyIterationsException object.
CsShape.TooManyIterationsException(Object[]) - Constructor for exception com.imsl.math.CsShape.TooManyIterationsException
Constructs a TooManyIterationsException object.
CsSmooth - Class in com.imsl.math
Extension of the Spline class to construct a smooth cubic spline from noisy data points.
CsSmooth(double[], double[]) - Constructor for class com.imsl.math.CsSmooth
Constructs a smooth cubic spline from noisy data using cross-validation to estimate the smoothing parameter.
CsSmooth(double[], double[], double[]) - Constructor for class com.imsl.math.CsSmooth
Constructs a smooth cubic spline from noisy data using cross-validation to estimate the smoothing parameter.
CsSmoothC2 - Class in com.imsl.math
Extension of the Spline class used to construct a spline for noisy data points using an alternate method.
CsSmoothC2(double[], double[], double) - Constructor for class com.imsl.math.CsSmoothC2
Constructs a smooth cubic spline from noisy data using an algorithm based on Reinsch (1967).
CsSmoothC2(double[], double[], double[], double) - Constructor for class com.imsl.math.CsSmoothC2
Constructs a smooth cubic spline from noisy data using an algorithm based on Reinsch (1967) with weights supplied by the user.
CsTCB - Class in com.imsl.math
Extension of the Spline class to handle a tension-continuity-bias (TCB) cubic spline, also known as a Kochanek-Bartels spline and is a generalization of the Catmull-Rom spline.
CsTCB(double[], double[]) - Constructor for class com.imsl.math.CsTCB
Constructs the tension-continuity-bias (TCB) cubic spline interpolant to the given data points.
CUBIC_SPLINE - Static variable in class com.imsl.stat.ARMAEstimateMissing
Indicates that missing values should be estimated using cublic spline interpolation.
cumipmt(double, int, double, int, int, int) - Static method in class com.imsl.finance.Finance
Returns the cumulative interest paid between two periods.
cumprinc(double, int, double, int, int, int) - Static method in class com.imsl.finance.Finance
Returns the cumulative principal paid between two periods.
CURRENT - Static variable in class com.imsl.math.Physical
 
currentType - Variable in class com.imsl.chart.Draw
 
CUSTOM - Static variable in class com.imsl.stat.TimeSeriesOperations.CombineMethod
Uses a custom combine function that is provided by the user.
CuSum - Class in com.imsl.chart.qc
CuSum is a cumulative sum chart.
CuSum(AxisXY, double[]) - Constructor for class com.imsl.chart.qc.CuSum
Creates a CuSum chart given the means of a series of samples.
CuSumStatus - Class in com.imsl.chart.qc
CuSumStatus is a cumulative sum status chart.
CuSumStatus(AxisXY, double[], double, double) - Constructor for class com.imsl.chart.qc.CuSumStatus
Creates a CuSumStatus chart.

D

d2 - Static variable in class com.imsl.chart.qc.ShewhartControlChart
This field contains d_{2,n} the mean of the ranges of n samples from a Gaussian distribution.
d3 - Static variable in class com.imsl.chart.qc.ShewhartControlChart
This field contains d_{3,n} the standard deviation of the ranges of n samples from a Gaussian distribution.
DASH_PATTERN_DASH - Static variable in class com.imsl.chart.ChartNode
Flag to draw a dashed line.
DASH_PATTERN_DASH_DOT - Static variable in class com.imsl.chart.ChartNode
Flag to draw a dash-dot pattern line.
DASH_PATTERN_DOT - Static variable in class com.imsl.chart.ChartNode
Flag to draw a dotted line.
DASH_PATTERN_SOLID - Static variable in class com.imsl.chart.ChartNode
Flag to draw solid line.
Data - Class in com.imsl.chart
Draws a data node.
Data(ChartNode) - Constructor for class com.imsl.chart.Data
Creates a data node.
Data(ChartNode, double[]) - Constructor for class com.imsl.chart.Data
Creates a data node with y values.
Data(ChartNode, ChartFunction, double, double) - Constructor for class com.imsl.chart.Data
Creates a data node with y values.
Data(ChartNode, double[], double[]) - Constructor for class com.imsl.chart.Data
Creates a data node with x and y values.
Data - Class in com.imsl.chart3d
Draws a 3D data node.
Data(AxisXYZ) - Constructor for class com.imsl.chart3d.Data
Creates a data node.
Data(AxisXYZ, double[], double[], double[]) - Constructor for class com.imsl.chart3d.Data
Creates a data node with x, y and z values.
Data.CustomMarkerFactory - Interface in com.imsl.chart3d
Factory to create customized markers.
DATA_TYPE_ERROR_X - Static variable in class com.imsl.chart.ErrorBar
Value for attribute "DataType" indicating that this is a horizontal error bar.
DATA_TYPE_ERROR_Y - Static variable in class com.imsl.chart.ErrorBar
Value for attribute "DataType" indicating that this is a vertical error bar.
DATA_TYPE_FILL - Static variable in class com.imsl.chart.ChartNode
Value for attribute "DataType" indicating that the area between the lines connecting the data points and the horizontal reference line (y = attribute "Reference") should be filled.
DATA_TYPE_LINE - Static variable in class com.imsl.chart.ChartNode
Value for attribute "DataType" indicating that the data points should be connected with line segments.
DATA_TYPE_LINE - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "DataType" indicating that the data points should be connected with line segments.
DATA_TYPE_MARKER - Static variable in class com.imsl.chart.ChartNode
Value for attribute "DataType" indicating that a marker should be drawn at each data point.
DATA_TYPE_MARKER - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "DataType" indicating that a marker should be drawn at each data point.
DATA_TYPE_PICTURE - Static variable in class com.imsl.chart.ChartNode
Value for attribute "DataType" indicating that an image (attribute "Image") should be drawn at each data point.
DATA_TYPE_PICTURE - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "DataType" indicating that an image (attribute "Image") should be drawn at each data point.
DATA_TYPE_TUBE - Static variable in class com.imsl.chart.ChartNode
Value for attribute "DataType" indicating that an a tube connecting the data points should be drawn.
DATA_TYPE_TUBE - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "DataType" indicating that a tube connecting the data points should be drawn.
dataRange(double[]) - Method in class com.imsl.chart.Bar
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.BarItem
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.BarSet
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.BoxPlot
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Contour
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Data
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Dendrogram
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.ErrorBar
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Heatmap
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.HighLowClose
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.qc.ControlLimit
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.qc.CuSum
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.qc.ShewhartControlChart
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Treemap
Updates the data range, range = {xmin,xmax,ymin,ymax} or range = {xmin,xmax,ymin,ymax,zmin,zmax}.
dataRange(double[]) - Method in class com.imsl.chart3d.Data
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart3d.Surface
Update the data range, range = {xmin,xmax,ymin,ymax}.
DAY - Static variable in class com.imsl.chart.HighLowClose
Milliseconds per day
DayCountBasis - Class in com.imsl.finance
The Day Count Basis.
DayCountBasis(BasisPart, BasisPart) - Constructor for class com.imsl.finance.DayCountBasis
Creates a new DayCountBasis.
daysBetween(GregorianCalendar, GregorianCalendar) - Method in interface com.imsl.finance.BasisPart
Returns the number of days from date1 to date2.
daysInPeriod(GregorianCalendar, int) - Method in interface com.imsl.finance.BasisPart
Returns the number of days in a coupon period.
db(double, double, int, int, int) - Static method in class com.imsl.finance.Finance
Returns the depreciation of an asset using the fixed-declining balance method.
ddb(double, double, int, int, double) - Static method in class com.imsl.finance.Finance
Returns the depreciation of an asset using the double-declining balance method.
DecisionTree - Class in com.imsl.datamining.decisionTree
Abstract class for generating a decision tree for a single response variable and one or more predictor variables.
DecisionTree(double[][], int, PredictiveModel.VariableType[]) - Constructor for class com.imsl.datamining.decisionTree.DecisionTree
Constructs a DecisionTree object for a single response variable and multiple predictor variables.
DecisionTree.MaxTreeSizeExceededException - Exception in com.imsl.datamining.decisionTree
Exception thrown when the maximum tree size has been exceeded.
DecisionTree.MaxTreeSizeExceededException(String) - Constructor for exception com.imsl.datamining.decisionTree.DecisionTree.MaxTreeSizeExceededException
Constructs a MaxTreeSizeExceededException and issues the specified message.
DecisionTree.MaxTreeSizeExceededException(String, Object[]) - Constructor for exception com.imsl.datamining.decisionTree.DecisionTree.MaxTreeSizeExceededException
Constructs a MaxTreeSizeExceededException with the specified detail message.
DecisionTree.PruningFailedToConvergeException - Exception in com.imsl.datamining.decisionTree
Exception thrown when pruning fails to converge.
DecisionTree.PruningFailedToConvergeException(String) - Constructor for exception com.imsl.datamining.decisionTree.DecisionTree.PruningFailedToConvergeException
Constructs a PruningFailedToConvergeException with the specified detail message.
DecisionTree.PureNodeException - Exception in com.imsl.datamining.decisionTree
Exception thrown when attempting to split a node that is already pure (response variable is constant).
DecisionTree.PureNodeException(String) - Constructor for exception com.imsl.datamining.decisionTree.DecisionTree.PureNodeException
Constructs a PureNodeException with the specified detail message.
DecisionTreeInfoGain - Class in com.imsl.datamining.decisionTree
Abstract class that extends DecisionTree for classes that use an information gain criteria.
DecisionTreeInfoGain(double[][], int, PredictiveModel.VariableType[]) - Constructor for class com.imsl.datamining.decisionTree.DecisionTreeInfoGain
Constructs a DecisionTree object for a single response variable and multiple predictor variables.
DecisionTreeInfoGain.GainCriteria - Class in com.imsl.datamining.decisionTree
Specifies which information gain criteria to use in determining the best split at each node.
DecisionTreeSurrogateMethod - Interface in com.imsl.datamining.decisionTree
Methods to account for missing values in predictor variables.
decode(double) - Method in class com.imsl.datamining.neural.ScaleFilter
Unscales a value.
decode(double[]) - Method in class com.imsl.datamining.neural.ScaleFilter
Unscales an array of values.
decode(int, double[][]) - Method in class com.imsl.datamining.neural.ScaleFilter
Unscales a single column of a two dimensional array of values.
decode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter
Decodes a binary encoded array into its nominal category.
decode(int[][]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter
Decodes a matrix representing the binary encoded columns of the nominal variable.
decode(double) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Decodes an encoded ordinal variable.
decode(double[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Decodes an array of encoded ordinal values.
defineConstant(String, Physical) - Static method in class com.imsl.math.Physical
Defines a new constant.
definePrefix(String, double) - Static method in class com.imsl.math.Physical
Defines a new prefix.
defineUnit(String, Physical) - Static method in class com.imsl.math.Physical
Defines a new unit.
deleteRow() - Method in class com.imsl.io.AbstractFlatFile
Deletes the current row from this ResultSet object and from the underlying database.
Dendrogram - Class in com.imsl.chart
A Dendrogram chart for cluster analysis.
Dendrogram(AxisXY, ClusterHierarchical) - Constructor for class com.imsl.chart.Dendrogram
Constructs a vertical dendrogram chart using supplied ClusterHierarchical object.
Dendrogram(AxisXY, double[], int[], int[]) - Constructor for class com.imsl.chart.Dendrogram
Constructs a vertical dendrogram chart using supplied data.
Dendrogram(AxisXY, ClusterHierarchical, int) - Constructor for class com.imsl.chart.Dendrogram
Constructs a dendrogram chart using supplied ClusterHierarchical object.
Dendrogram(AxisXY, double[], int[], int[], int) - Constructor for class com.imsl.chart.Dendrogram
Constructs a dendrogram chart using supplied data.
DENDROGRAM_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.ChartNode
Flag to indicate a horizontal dendrogram.
DENDROGRAM_TYPE_VERTICAL - Static variable in class com.imsl.chart.ChartNode
Flag to indicate a vertical dendrogram.
DenseLP - Class in com.imsl.math
Solves a linear programming problem using an active set strategy.
DenseLP(MPSReader) - Constructor for class com.imsl.math.DenseLP
Constructor using an MPSReader object.
DenseLP(double[][], double[], double[]) - Constructor for class com.imsl.math.DenseLP
Constructor variables of type double.
DenseLP.AllConstraintsNotSatisfiedException - Exception in com.imsl.math
All constraints are not satisfied.
DenseLP.AllConstraintsNotSatisfiedException() - Constructor for exception com.imsl.math.DenseLP.AllConstraintsNotSatisfiedException
All constraints are not satisfied.
DenseLP.AllConstraintsNotSatisfiedException(String) - Constructor for exception com.imsl.math.DenseLP.AllConstraintsNotSatisfiedException
All constraints are not satisfied.
DenseLP.AllConstraintsNotSatisfiedException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.AllConstraintsNotSatisfiedException
All constraints are not satisfied.
DenseLP.BoundsInconsistentException - Exception in com.imsl.math
The bounds given are inconsistent.
DenseLP.BoundsInconsistentException(String) - Constructor for exception com.imsl.math.DenseLP.BoundsInconsistentException
The bounds given are inconsistent.
DenseLP.BoundsInconsistentException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.BoundsInconsistentException
The bounds given are inconsistent.
DenseLP.CyclingOccurringException - Exception in com.imsl.math
The algorithm appears to be cycling.
DenseLP.CyclingOccurringException() - Constructor for exception com.imsl.math.DenseLP.CyclingOccurringException
The algorithm appears to be cycling.
DenseLP.CyclingOccurringException(String) - Constructor for exception com.imsl.math.DenseLP.CyclingOccurringException
The algorithm appears to be cycling.
DenseLP.CyclingOccurringException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.CyclingOccurringException
The algorithm appears to be cycling.
DenseLP.MultipleSolutionsException - Exception in com.imsl.math
The problem has multiple solutions giving essentially the same minimum.
DenseLP.MultipleSolutionsException() - Constructor for exception com.imsl.math.DenseLP.MultipleSolutionsException
The problem has multiple solutions giving essentially the same minimum.
DenseLP.MultipleSolutionsException(String) - Constructor for exception com.imsl.math.DenseLP.MultipleSolutionsException
The problem has multiple solutions giving essentially the same minimum.
DenseLP.MultipleSolutionsException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.MultipleSolutionsException
The problem has multiple solutions giving essentially the same minimum.
DenseLP.NoAcceptablePivotException - Exception in com.imsl.math
No acceptable pivot could be found.
DenseLP.NoAcceptablePivotException() - Constructor for exception com.imsl.math.DenseLP.NoAcceptablePivotException
No acceptable pivot could be found.
DenseLP.NoAcceptablePivotException(String) - Constructor for exception com.imsl.math.DenseLP.NoAcceptablePivotException
No acceptable pivot could be found.
DenseLP.NoAcceptablePivotException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.NoAcceptablePivotException
No acceptable pivot could be found.
DenseLP.ProblemUnboundedException - Exception in com.imsl.math
The problem is unbounded.
DenseLP.ProblemUnboundedException() - Constructor for exception com.imsl.math.DenseLP.ProblemUnboundedException
The problem is unbounded.
DenseLP.ProblemUnboundedException(String) - Constructor for exception com.imsl.math.DenseLP.ProblemUnboundedException
The problem is unbounded.
DenseLP.ProblemUnboundedException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.ProblemUnboundedException
The problem is unbounded.
DenseLP.ProblemVacuousException - Exception in com.imsl.math
The problem is vaxuous.
DenseLP.ProblemVacuousException() - Constructor for exception com.imsl.math.DenseLP.ProblemVacuousException
The problem is vaxuous.
DenseLP.ProblemVacuousException(String) - Constructor for exception com.imsl.math.DenseLP.ProblemVacuousException
The problem is vaxuous.
DenseLP.ProblemVacuousException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.ProblemVacuousException
The problem is vaxuous.
DenseLP.SomeConstraintsDiscardedException - Exception in com.imsl.math
Some constraints were discarded because they were too linearly dependent on other active constraints.
DenseLP.SomeConstraintsDiscardedException() - Constructor for exception com.imsl.math.DenseLP.SomeConstraintsDiscardedException
Some constraints were discarded because they were too linearly dependent on other active constraints.
DenseLP.SomeConstraintsDiscardedException(String) - Constructor for exception com.imsl.math.DenseLP.SomeConstraintsDiscardedException
Some constraints were discarded because they were too linearly dependent on other active constraints.
DenseLP.SomeConstraintsDiscardedException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.SomeConstraintsDiscardedException
Some constraints were discarded because they were too linearly dependent on other active constraints.
derivative(double, double) - Method in interface com.imsl.datamining.neural.Activation
Returns the value of the derivative of the activation function.
derivative(double) - Method in class com.imsl.math.BSpline
Returns the value of the first derivative of the B-spline at a point.
derivative(double, int) - Method in class com.imsl.math.BSpline
Returns the value of the derivative of the B-spline at a point.
derivative(double[], int) - Method in class com.imsl.math.BSpline
Returns the value of the derivative of the B-spline at each point of an array.
derivative(double) - Method in class com.imsl.math.Spline
Returns the value of the first derivative of the spline at a point.
derivative(double, int) - Method in class com.imsl.math.Spline
Returns the value of the derivative of the spline at a point.
derivative(double[], int) - Method in class com.imsl.math.Spline
Returns the value of the derivative of the spline at each point of an array.
derivative(double, double, int, int) - Method in class com.imsl.math.Spline2D
Returns the value of the partial derivative of the tensor-product spline at the point (x, y).
derivative(double[], double[], int, int) - Method in class com.imsl.math.Spline2D
Returns the values of the partial derivative of the tensor-product spline of an array of points.
derivative(double[], int, double[], double[], double[]) - Method in interface com.imsl.stat.NonlinearRegression.Derivative
Computes the weight, frequency, and partial derivatives of the residual given the parameter vector theta for a single observation.
descending(int[]) - Static method in class com.imsl.stat.Sort
Sorts an integer array into descending order.
descending(int[], int[]) - Static method in class com.imsl.stat.Sort
Sorts an integer array into descending order and returns the permutation vector.
descending(double[]) - Static method in class com.imsl.stat.Sort
Sorts an array into descending order.
descending(double[], int[]) - Static method in class com.imsl.stat.Sort
Sorts an array into descending order and returns the permutation vector.
descending(double[][], int) - Static method in class com.imsl.stat.Sort
Sorts a matrix into descending order by the first nkeys.
descending(double[][], int[]) - Static method in class com.imsl.stat.Sort
Sorts a matrix into descending order by specified keys.
descending(double[][], int, int[]) - Static method in class com.imsl.stat.Sort
Sorts a matrix into descending order by the first nkeys and returns the permutation vector.
descending(double[][], int[], int[]) - Static method in class com.imsl.stat.Sort
Sorts a matrix into descending order by specified keys and return the permutation vector.
determinant() - Method in class com.imsl.math.ComplexLU
Return the determinant of the matrix used to construct this instance.
determinant() - Method in class com.imsl.math.LU
Return the determinant of the matrix used to construct this instance.
DEVIANCE - Static variable in class com.imsl.datamining.decisionTree.DecisionTreeInfoGain.GainCriteria
A measure of the quality of fit.
diagonal(int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a diagonal pattern.
diamond(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a diamond pattern (a checkerboard rotated 45 degrees).
diamondHatch(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a crosshatch on a 45 degree angle.
DIFF - Static variable in class com.imsl.stat.TimeSeriesOperations.CombineMethod
Takes the difference (ts1-ts2) of the two values.
Difference - Class in com.imsl.stat
Differences a seasonal or nonseasonal time series.
Difference() - Constructor for class com.imsl.stat.Difference
Constructor for Difference.
dim - Variable in class com.imsl.math.Physical
 
DIRECT_AT_RESTART_AND_TERMINATION - Static variable in class com.imsl.math.GenMinRes
Indicates residual updating is to be done by direct evaluation upon restarting and at termination.
DIRECT_AT_RESTART_ONLY - Static variable in class com.imsl.math.GenMinRes
Indicates residual updating is to be done by direct evaluation upon restarting only.
DirectionalLight - Class in com.imsl.chart3d
A directional light.
DirectionalLight(Chart3D) - Constructor for class com.imsl.chart3d.DirectionalLight
Creates a directional light pointing in the negative z direction.
DirectionalLight(Chart3D, double, double, double) - Constructor for class com.imsl.chart3d.DirectionalLight
Creates a directional light pointing with a specified direction.
disc(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the implied interest rate of a discount bond.
discreteUniform(int, int) - Static method in class com.imsl.stat.Cdf
Evaluates the discrete uniform cumulative probability distribution function.
discreteUniform(double, int) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the discrete uniform cumulative probability distribution function.
discreteUniform(int, int) - Static method in class com.imsl.stat.Pdf
Evaluates the discrete uniform probability density function.
DiscriminantAnalysis - Class in com.imsl.stat
Performs a linear or a quadratic discriminant function analysis among several known groups.
DiscriminantAnalysis(int, int) - Constructor for class com.imsl.stat.DiscriminantAnalysis
Constructs a DiscriminantAnalysis.
DiscriminantAnalysis.CovarianceSingularException - Exception in com.imsl.stat
The variance-covariance matrix is singular.
DiscriminantAnalysis.CovarianceSingularException(String) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException
The variance-covariance matrix is singular.
DiscriminantAnalysis.CovarianceSingularException(String, Object[]) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException
The variance-covariance matrix is singular.
DiscriminantAnalysis.EmptyGroupException - Exception in com.imsl.stat
There are no observations in a group.
DiscriminantAnalysis.EmptyGroupException(String) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.EmptyGroupException
There are no observations in a group.
DiscriminantAnalysis.EmptyGroupException(String, Object[]) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.EmptyGroupException
There are no observations in a group.
DiscriminantAnalysis.SumOfWeightsNegException - Exception in com.imsl.stat
The sum of the weights have become negative.
DiscriminantAnalysis.SumOfWeightsNegException(String) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException
The sum of the weights have become negative.
DiscriminantAnalysis.SumOfWeightsNegException(String, Object[]) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException
The sum of the weights have become negative.
Dissimilarities - Class in com.imsl.stat
Computes a matrix of dissimilarities (or similarities) between the columns (or rows) of a matrix.
Dissimilarities(double[][]) - Constructor for class com.imsl.stat.Dissimilarities
Constructor for Dissimilarities.
Dissimilarities.NoPositiveVarianceException - Exception in com.imsl.stat
No variable has positive variance.
Dissimilarities.NoPositiveVarianceException() - Constructor for exception com.imsl.stat.Dissimilarities.NoPositiveVarianceException
Constructs a NoPositiveVarianceException.
Dissimilarities.ScaleFactorZeroException - Exception in com.imsl.stat
The computations cannot continue because a scale factor is zero.
Dissimilarities.ScaleFactorZeroException(int) - Constructor for exception com.imsl.stat.Dissimilarities.ScaleFactorZeroException
Constructs a ScaleFactorZeroException.
Dissimilarities.ZeroNormException - Exception in com.imsl.stat
The computations cannot continue because the Euclidean norm of the column is equal to zero.
Dissimilarities.ZeroNormException(int) - Constructor for exception com.imsl.stat.Dissimilarities.ZeroNormException
Constructs a ZeroNormException.
Distribution - Interface in com.imsl.stat
Public interface for the user-supplied distribution function.
divide(Complex, Complex) - Static method in class com.imsl.math.Complex
Returns the result of a Complex object divided by a Complex object, x/y.
divide(Complex, double) - Static method in class com.imsl.math.Complex
Returns the result of a Complex object divided by a double, x/y.
divide(double, Complex) - Static method in class com.imsl.math.Complex
Returns the result of a double divided by a Complex object, x/y.
divide(Physical, Physical) - Static method in class com.imsl.math.Physical
Divide two Physical objects.
divide(Physical, double) - Static method in class com.imsl.math.Physical
Divide a Physical object by a double.
divide(double, Physical) - Static method in class com.imsl.math.Physical
Divide a double by a Physical object.
doGet(HttpServletRequest, HttpServletResponse) - Method in class com.imsl.chart.ChartServlet
Returns the chart as a PNG image.
doGetBytes(int) - Method in class com.imsl.io.AbstractFlatFile
Implements the actual getBytes().
doGetBytes(int) - Method in class com.imsl.io.FlatFile
Gets the value of the designated column in the current row as a byte array.
dollarde(double, int) - Static method in class com.imsl.finance.Finance
Converts a fractional price to a decimal price.
dollarfr(double, int) - Static method in class com.imsl.finance.Finance
Converts a decimal price to a fractional price.
doNext() - Method in class com.imsl.io.AbstractFlatFile
Implements the operations on the file required by the method next().
doNext() - Method in class com.imsl.io.FlatFile
Moves the cursor down one row from its current position.
dot(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a pattern that is an array of circles.
doubleValue() - Method in class com.imsl.math.Complex
Returns the value of the real part as a double.
doubleValue() - Method in class com.imsl.math.Physical
Returns the value of this dimensionless object.
downdate(double[]) - Method in class com.imsl.math.Cholesky
Downdates the factorization by subtracting a rank-1 matrix.
downdate(double[][], int[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Removes a set of observations from the discriminant functions.
downdate(double[][], int[], int[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Removes a set of observations from the discriminant functions.
downdate(double[][], int[], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Removes a set of observations and associated frequencies and weights from the discriminant functions.
downdate(double[][], int[], int[], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Removes a set of observations and associated frequencies and weights from the discriminant functions.
downdateX(double[]) - Method in class com.imsl.stat.NormTwoSample
Removes the observations in x from the first sample.
downdateY(double[]) - Method in class com.imsl.stat.NormTwoSample
Removes the observations in y from the second sample.
Draw - Class in com.imsl.chart
Chart tree renderer.
Draw(Graphics, Dimension) - Constructor for class com.imsl.chart.Draw
Contructs a Draw object.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.Draw
Draws the outline of a circular or elliptical arc covering the specified rectangle.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawMap
Draws the outline of a circular or elliptical arc covering the specified rectangle.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawPick
Draw an arc.
drawClippedImage(Image, int, int) - Method in class com.imsl.chart.Draw
Draws an image such that any portion of the image beyond the axis range is clipped.
drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.Draw
Draw an error bar.
drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.DrawMap
Draw an error bar.
drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.DrawPick
Draw ErrorBar
drawImage(Image, int, int) - Method in class com.imsl.chart.Draw
Draw an image.
drawImage(Image, int, int) - Method in class com.imsl.chart.DrawMap
Draw Image
drawImage(Image, int, int) - Method in class com.imsl.chart.DrawPick
Draw Image
drawLine(int, int, int, int) - Method in class com.imsl.chart.Draw
Draw a line from (x0,y0) to (x1,y1).
drawLine(int, int, int, int) - Method in class com.imsl.chart.DrawMap
Draw a line from (x0,y0) to (x1,y1).
drawLine(int, int, int, int) - Method in class com.imsl.chart.DrawPick
Draw a line from (x0,y0) to (x1,y1).
DrawMap - Class in com.imsl.chart
Creates an HTML client-side imagemap from a chart tree.
DrawMap(Graphics, Dimension) - Constructor for class com.imsl.chart.DrawMap
Contructs a DrawMap object.
drawMarker(int, int) - Method in class com.imsl.chart.Draw
Draw a marker.
drawMarker(int, int) - Method in class com.imsl.chart.DrawMap
Draw a marker.
drawMarker(int, int) - Method in class com.imsl.chart.DrawPick
Draw a marker.
DrawPick - Class in com.imsl.chart
The DrawPick class.
DrawPick(MouseEvent, Graphics, Dimension) - Constructor for class com.imsl.chart.DrawPick
Contructs a DrawPick object.
drawRotatedText(Text, int, int, float) - Method in class com.imsl.chart.Draw
Draws a text object, at the specified angle, with its lower left point being at (x,y).
drawText(Text, int, int) - Method in class com.imsl.chart.Draw
Draws a text object.
drawText(Text, int, int, boolean) - Method in class com.imsl.chart.Draw
Draws a text object.
drawText(Graphics, Text) - Method in class com.imsl.chart.Draw
Draws the text.
drawText(Text, int, int, boolean) - Method in class com.imsl.chart.DrawMap
 
drawText(Text, int, int) - Method in class com.imsl.chart.DrawPick
 
DUNN_SIDAK - Static variable in class com.imsl.stat.ANOVA
The Dunn-Sidak method
duration(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the Macaulay duration of a security where the security has periodic interest payments.

E

E - Static variable in class com.imsl.math.JMath
 
effect(double, int) - Static method in class com.imsl.finance.Finance
Returns the effective annual interest rate.
Eigen - Class in com.imsl.math
Collection of Eigen System functions.
Eigen() - Constructor for class com.imsl.math.Eigen
Constructs the eigenvalues and the eigenvectors of a real square matrix.
Eigen.DidNotConvergeException - Exception in com.imsl.math
The iteration did not converge
Eigen.DidNotConvergeException(String) - Constructor for exception com.imsl.math.Eigen.DidNotConvergeException
Constructs a DidNotConvergeException object.
Eigen.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.math.Eigen.DidNotConvergeException
Constructs a DidNotConvergeException object.
EmpiricalQuantiles - Class in com.imsl.stat
Computes empirical quantiles.
EmpiricalQuantiles(double[], double[]) - Constructor for class com.imsl.stat.EmpiricalQuantiles
Constructor for EmpiricalQuantiles.
EmpiricalQuantiles.ScaleFactorZeroException - Exception in com.imsl.stat
The computations cannot continue because a scale factor is zero.
EmpiricalQuantiles.ScaleFactorZeroException(int) - Constructor for exception com.imsl.stat.EmpiricalQuantiles.ScaleFactorZeroException
Constructs a ScaleFactorZeroException.
encode(double) - Method in class com.imsl.datamining.neural.ScaleFilter
Scales a value.
encode(double[]) - Method in class com.imsl.datamining.neural.ScaleFilter
Scales an array of values.
encode(int, double[][]) - Method in class com.imsl.datamining.neural.ScaleFilter
Scales a single column of a two dimensional array of values.
encode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter
Encodes class data prior to its use in neural network training.
encode(int) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter
Apply forward encoding to a value.
encode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Encodes an array of ordinal categories into an array of transformed percentages.
encode(int) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Encodes an ordinal category.
END_COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a column label is to be returned.
END_COLUMN_LABELS - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a column label row is to be returned.
END_ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatted string for ending an entry is to be returned.
END_MATRIX - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a matrix is to be returned.
END_ROW - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a row is to be returned.
END_ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a row label is to be returned.
endErrorBar() - Method in class com.imsl.chart.Draw
Stop drawing an error bar.
endErrorBar() - Method in class com.imsl.chart.DrawMap
 
endErrorBar() - Method in class com.imsl.chart.DrawPick
End ErrorBar
endFill() - Method in class com.imsl.chart.Draw
Stop drawing a filled region.
endFill() - Method in class com.imsl.chart.DrawMap
 
endFill() - Method in class com.imsl.chart.DrawPick
End fill
endImage() - Method in class com.imsl.chart.Draw
Stop drawing an image.
endImage() - Method in class com.imsl.chart.DrawMap
 
endImage() - Method in class com.imsl.chart.DrawPick
End Image
endLine() - Method in class com.imsl.chart.Draw
Finish drawing lines.
endLine() - Method in class com.imsl.chart.DrawMap
 
endLine() - Method in class com.imsl.chart.DrawPick
Finish drawing lines.
endMarker() - Method in class com.imsl.chart.Draw
Finish drawing markers.
endMarker() - Method in class com.imsl.chart.DrawMap
 
endMarker() - Method in class com.imsl.chart.DrawPick
Finish drawing markers.
endText() - Method in class com.imsl.chart.Draw
Stop drawing text.
endText() - Method in class com.imsl.chart.DrawMap
 
endText() - Method in class com.imsl.chart.DrawPick
End Text
ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatted string for a given entry is to be returned.
EpochTrainer - Class in com.imsl.datamining.neural
Two-stage training using randomly selected training patterns in stage I.
EpochTrainer(Trainer) - Constructor for class com.imsl.datamining.neural.EpochTrainer
Creates a single stage EpochTrainer.
EpochTrainer(Trainer, Trainer) - Constructor for class com.imsl.datamining.neural.EpochTrainer
Creates an two-stage EpochTrainer.
EPSILON_LARGE - Static variable in class com.imsl.math.Sfun
The largest relative spacing for doubles.
EPSILON_LARGE - Static variable in class com.imsl.math.Spline
The largest relative spacing for double.
EPSILON_SMALL - Static variable in class com.imsl.math.QuadraticProgramming
The smallest relative spacing for doubles.
EPSILON_SMALL - Static variable in class com.imsl.math.Sfun
The smallest relative spacing for doubles.
EPSILON_SMALL - Static variable in class com.imsl.math.ZeroPolynomial
The smallest relative spacing for doubles.
EpsilonAlgorithm - Class in com.imsl.math
The class is used to determine the limit of a sequence of approximations, by means of the Epsilon algorithm of P.
EpsilonAlgorithm() - Constructor for class com.imsl.math.EpsilonAlgorithm
Initializes an EpsilonAlgorithm with a maximum table size of 50.
EpsilonAlgorithm(int) - Constructor for class com.imsl.math.EpsilonAlgorithm
Initializes an EpsilonAlgorithm.
equals(Complex) - Method in class com.imsl.math.Complex
Compares with another Complex.
equals(Object) - Method in class com.imsl.math.Complex
Compares this object against the specified object.
erf(double) - Static method in class com.imsl.math.Sfun
Returns the error function of a double.
erfc(double) - Static method in class com.imsl.math.Sfun
Returns the complementary error function of a double.
erfce(double) - Static method in class com.imsl.math.Sfun
Returns the exponentially scaled complementary error function.
erfcInverse(double) - Static method in class com.imsl.math.Sfun
Returns the inverse of the complementary error function.
erfInverse(double) - Static method in class com.imsl.math.Sfun
Returns the inverse of the error function.
error(String, Object[]) - Method in class com.imsl.chart.xml.ChartXML
Handles error messages.
error(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML
Receive notification of a recoverable error.
error(double[], double[]) - Method in interface com.imsl.datamining.neural.QuasiNewtonTrainer.Error
Returns the contribution to the error from a single training output target.
ERROR_BAR - Static variable in class com.imsl.chart.Draw
 
ERROR_NORM_ABS - Static variable in class com.imsl.math.ODE
Used by method setNorm to indicate that the error norm to be used is to be the absolute error, equals max(|e_i|)
ERROR_NORM_EUCLIDEAN - Static variable in class com.imsl.math.ODE
Used by method setNorm to indicate that the error norm to be used is to be the scaled Euclidean norm defined as

{s = sqrt {sum_{i=1}^{neq}{frac{{e_i}^2}{{w_i}^2}}}}

ERROR_NORM_MAX - Static variable in class com.imsl.math.ODE
Used by method setNorm to indicate that the error norm to be used is to be the maximum of e_i/max(|y_i(t)|, floor) where floor is set via setFloor
ERROR_NORM_MINABSREL - Static variable in class com.imsl.math.ODE
Used by method setNorm to indicate that the error norm to be used is to be the minimum of the absolute error and the relative error, equals the maximum of e_i/max(|y_i(t)|, 1)
ErrorBar - Class in com.imsl.chart
Data points with error bars.
ErrorBar(AxisXY, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.ErrorBar
Creates a set of error bars centered at (x[k],y[k]) and with extents low[k],high[k].
errorGradient(double[], double[]) - Method in interface com.imsl.datamining.neural.QuasiNewtonTrainer.Error
Returns the derivative of the error function with respect to the forecast output.
eval(HyperRectangleQuadrature.Function) - Method in class com.imsl.math.HyperRectangleQuadrature
Returns the value of the integral over the unit cube.
eval(HyperRectangleQuadrature.Function, double[], double[]) - Method in class com.imsl.math.HyperRectangleQuadrature
Returns the value of the integral over a cube.
eval(Quadrature.Function, double, double) - Method in class com.imsl.math.Quadrature
Returns the value of the integral from a to b.
eval(double[]) - Method in interface com.imsl.stat.Distribution
Evaluation method to fit the user-supplied probability density function to input data
eval(double[]) - Method in class com.imsl.stat.GammaDistribution
Fits a gamma probability distribution to xData and returns the probability density at each value.
eval(double[], Object[]) - Method in class com.imsl.stat.GammaDistribution
Evaluates a gamma probability distribution with a given set of parameters at each point in xData and returns the probability density at each value.
eval(double, Object[]) - Method in class com.imsl.stat.GammaDistribution
Evaluates a gamma probability density at a given point xData.
eval(double, double) - Method in class com.imsl.stat.InverseCdf
Evaluates the inverse CDF function.
eval(double[]) - Method in class com.imsl.stat.LogNormalDistribution
Fits a lognormal probability distribution to xData and returns the probability density at each value.
eval(double[], Object[]) - Method in class com.imsl.stat.LogNormalDistribution
Evaluates a lognormal probability distribution with a given set of parameters at each point in xData and returns the probability density at each value.
eval(double, Object[]) - Method in class com.imsl.stat.LogNormalDistribution
Evaluates a lognormal probability density function at a given point xData.
eval(double[]) - Method in class com.imsl.stat.NormalDistribution
Fits a normal (Gaussian) probability distribution to xData and returns the probability density at each value.
eval(double[], Object[]) - Method in class com.imsl.stat.NormalDistribution
Evaluates a normal (Gaussian) probability distribution with the given parameters at each point in xData and returns the probability density at each value.
eval(double, Object[]) - Method in class com.imsl.stat.NormalDistribution
Evaluates a normal (Gaussian) probability density at a given point xData.
eval(double[]) - Method in class com.imsl.stat.PoissonDistribution
Fits a Poisson probability distribution to xData and returns the probability density at each value.
eval(double[], Object[]) - Method in class com.imsl.stat.PoissonDistribution
Evaluates a Poisson probability distribution with a given set of parameters at each point in xData and returns the probability density at each value.
eval(double, Object[]) - Method in class com.imsl.stat.PoissonDistribution
Evaluates a Poisson probability density function at a given point xData.
eval(double[], Object[]) - Method in interface com.imsl.stat.ProbabilityDistribution
Evaluates the user-supplied probability density of each value in xData using the supplied probability distribution parameters.
eval(double, Object[]) - Method in interface com.imsl.stat.ProbabilityDistribution
Evaluation method for the user-supplied distribution function and parameters.
evaluateCDF() - Method in class com.imsl.stat.KaplanMeierECDF
Computes the empirical CDF and returns the CDF values up to, but not including the time values returned by getTimes.
evaluateF(int, double[]) - Method in class com.imsl.math.NumericalDerivatives
This method is provided by the user to compute the function values at the current independent variable values y.
evaluateJ(double[]) - Method in class com.imsl.math.NumericalDerivatives
Evaluates the Jacobian for a system of (m) equations in (n) variables.
EWMA - Class in com.imsl.chart.qc
EWMA is an exponentially weighted moving average control chart.
EWMA(AxisXY, double[], double) - Constructor for class com.imsl.chart.qc.EWMA
Creates an exponentially weighted moving average chart.
EWMA(AxisXY, double[], double, double, double) - Constructor for class com.imsl.chart.qc.EWMA
Creates an exponentially weighted moving average chart using the given values for the expected mean and standard deviation.
EXACT_MATCHES - Static variable in class com.imsl.stat.Dissimilarities
Indicates the number of exact matches distance method.
examineStep(int, double, double[]) - Method in class com.imsl.math.ODE
Called before and after each internal step.
excludeFirst(boolean) - Method in class com.imsl.stat.Difference
If set to true, the observations lost due to differencing will be excluded.
exp(Complex) - Static method in class com.imsl.math.Complex
Returns the exponential of a Complex z, exp(z).
exp(double) - Static method in class com.imsl.math.JMath
Returns the exponential of a double.
expectedNormalOrderStatistic(int, int) - Static method in class com.imsl.stat.Ranks
Returns the expected value of a normal order statistic.
expm1(double) - Static method in class com.imsl.math.Hyperbolic
Returns exp(x)-1, the exponential of x minus 1.
exponential(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the exponential cumulative probability distribution function.
exponential(double, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the exponential cumulative probability distribution function.
exponential(double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the exponential probability density function
extrapolate(double) - Method in class com.imsl.math.EpsilonAlgorithm
Extrapolates the convergence limit of a sequence.
extremeValue(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the extreme value cumulative probability distribution function.
extremeValue(double, double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the extreme value cumulative probability distribution function.
extremeValue(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the extreme value probability density function.

F

f(double) - Method in interface com.imsl.chart.ChartFunction
Function to be charted.
f(double) - Method in class com.imsl.chart.ChartSpline
Function to be charted.
f(double, double) - Method in interface com.imsl.chart3d.Surface.ZFunction
Define the surface function.
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockGradObjective
 
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockObjective
 
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective
 
f(double[]) - Method in interface com.imsl.math.HyperRectangleQuadrature.Function
Returns the value of the function at the given point.
f(double[]) - Method in interface com.imsl.math.MinConGenLin.Function
Public interface for the function to be minimized.
f(double[], int, boolean[]) - Method in interface com.imsl.math.MinConNLP.Function
Compute the value of the function at the given point.
f(double) - Method in interface com.imsl.math.MinUncon.Function
Public interface for the smooth function of a single variable to be minimized.
f(double[]) - Method in interface com.imsl.math.MinUnconMultiVar.Function
Public interface for the multivariate function to be minimized.
f(double[], double[]) - Method in interface com.imsl.math.NonlinLeastSquares.Function
Public interface for the nonlinear least-squares function.
f(int, double[]) - Method in interface com.imsl.math.NumericalDerivatives.Function
Returns the equations evaluated at the point y.
f(double, double[]) - Method in interface com.imsl.math.OdeAdamsGear.Function
Computes the value of the function y^{'} = f(t,y) at the given point.
f(double, double[], double[]) - Method in interface com.imsl.math.OdeRungeKutta.Function
Returns the value of the function at the given point.
f(double) - Method in interface com.imsl.math.Quadrature.Function
Returns the value of the function at the given point.
f(double) - Method in interface com.imsl.math.RadialBasis.Function
A radial basis function.
f(double) - Method in class com.imsl.math.RadialBasis.Gaussian
A Gaussian basis function.
f(double) - Method in class com.imsl.math.RadialBasis.HardyMultiquadric
A Hardy multiquadric basis function.
f(double) - Method in interface com.imsl.math.ZerosFunction.Function
Returns the value of the function at the given point.
f(double[], double[]) - Method in interface com.imsl.math.ZeroSystem.Function
Returns the value of the function at the given point.
F(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the F cumulative probability distribution function.
F(double, double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the F cumulative probability distribution function.
f(double[], int, double[], double[], double[]) - Method in interface com.imsl.stat.NonlinearRegression.Function
Computes the weight, frequency, and residual given the parameter vector theta for a single observation.
F(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the F probability density function.
FACE_XA - Static variable in class com.imsl.chart3d.AxisBox
Show the x = a face of the box.
FACE_XB - Static variable in class com.imsl.chart3d.AxisBox
Show the x = b face of the box.
FACE_YA - Static variable in class com.imsl.chart3d.AxisBox
Show the y = a face of the box.
FACE_YB - Static variable in class com.imsl.chart3d.AxisBox
Show the y = b face of the box.
FACE_ZA - Static variable in class com.imsl.chart3d.AxisBox
Show the z = a face of the box.
FACE_ZB - Static variable in class com.imsl.chart3d.AxisBox
Show the z = b face of the box.
fact(int) - Static method in class com.imsl.math.Sfun
Returns the factorial of an integer.
factor - Variable in class com.imsl.math.ComplexLU
This is an n by n Complex matrix containing the LU factorization of the matrix A.
factor - Variable in class com.imsl.math.LU
This is an n by n matrix containing the LU factorization of the matrix A.
FactorAnalysis - Class in com.imsl.stat
Performs Principal Component Analysis or Factor Analysis on a covariance or correlation matrix.
FactorAnalysis(double[][], int, int) - Constructor for class com.imsl.stat.FactorAnalysis
Constructor for FactorAnalysis.
FactorAnalysis.BadVarianceException - Exception in com.imsl.stat
Bad variance error.
FactorAnalysis.BadVarianceException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.BadVarianceException
Constructs a BadVarianceException object.
FactorAnalysis.BadVarianceException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.BadVarianceException
Constructs a BadVarianceException object.
FactorAnalysis.EigenvalueException - Exception in com.imsl.stat
Eigenvalue error.
FactorAnalysis.EigenvalueException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.EigenvalueException
Constructs a EigenvalueException object.
FactorAnalysis.EigenvalueException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.EigenvalueException
Constructs a EigenvalueException object.
FactorAnalysis.NonPositiveEigenvalueException - Exception in com.imsl.stat
Non positive eigenvalue error.
FactorAnalysis.NonPositiveEigenvalueException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException
Constructs a NonPositiveEigenvalueException object.
FactorAnalysis.NonPositiveEigenvalueException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException
Constructs a NonPositiveEigenvalueException object.
FactorAnalysis.NotPositiveSemiDefiniteException - Exception in com.imsl.stat
Covariance matrix not positive semi-definite.
FactorAnalysis.NotPositiveSemiDefiniteException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException
Constructs a NotPositiveSemiDefiniteException object.
FactorAnalysis.NotPositiveSemiDefiniteException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException
Constructs a NotPositiveSemiDefiniteException object.
FactorAnalysis.NotSemiDefiniteException - Exception in com.imsl.stat
Hessian matrix not semi-definite.
FactorAnalysis.NotSemiDefiniteException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.NotSemiDefiniteException
Constructs a NotSemiDefiniteException object.
FactorAnalysis.NotSemiDefiniteException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.NotSemiDefiniteException
Constructs a NotSemiDefiniteException object.
FactorAnalysis.RankException - Exception in com.imsl.stat
Rank of covariance matrix error.
FactorAnalysis.RankException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.RankException
Constructs a RankException object.
FactorAnalysis.RankException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.RankException
Constructs a RankException object.
FactorAnalysis.SingularException - Exception in com.imsl.stat
Covariance matrix singular error.
FactorAnalysis.SingularException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.SingularException
Constructs a SingularException object.
FactorAnalysis.SingularException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.SingularException
Constructs a SingularException object.
factorNumerically() - Method in class com.imsl.math.ComplexSparseCholesky
Computes the numeric factorization of a sparse Hermitian positive definite matrix.
factorNumerically() - Method in class com.imsl.math.SparseCholesky
Computes the numeric factorization of a sparse real symmetric positive definite matrix.
factorSymbolically() - Method in class com.imsl.math.ComplexSparseCholesky
Computes the symbolic factorization of a sparse Hermitian positive definite matrix.
factorSymbolically() - Method in class com.imsl.math.SparseCholesky
Computes the symbolic factorization of a sparse real symmetric positive definite matrix.
fatalError(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML
Receive notification of a non-recoverable error.
FaureSequence - Class in com.imsl.stat
Generates the low-discrepancy Faure sequence.
FaureSequence(int) - Constructor for class com.imsl.stat.FaureSequence
Creates a Faure sequence with the default base.
FaureSequence(int, int, int) - Constructor for class com.imsl.stat.FaureSequence
Creates a Faure sequence.
FeedForwardNetwork - Class in com.imsl.datamining.neural
A representation of a feed forward neural network.
FeedForwardNetwork() - Constructor for class com.imsl.datamining.neural.FeedForwardNetwork
Creates a new instance of FeedForwardNetwork.
FeynmanKac - Class in com.imsl.math
Solves the generalized Feynman-Kac PDE.
FeynmanKac(FeynmanKac.PdeCoefficients) - Constructor for class com.imsl.math.FeynmanKac
Constructs a PDE solver to solve the Feynman-Kac PDE.
FeynmanKac.Boundaries - Interface in com.imsl.math
Public interface for user supplied boundary coefficients and terminal condition the PDE must satisfy.
FeynmanKac.BoundaryInconsistentException - Exception in com.imsl.math
The boundary conditions are inconsistent.
FeynmanKac.BoundaryInconsistentException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.BoundaryInconsistentException
The boundary conditions are inconsistent.
FeynmanKac.ConstraintsInconsistentException - Exception in com.imsl.math
The constraints are inconsistent.
FeynmanKac.ConstraintsInconsistentException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.ConstraintsInconsistentException
The constraints are inconsistent.
FeynmanKac.CorrectorConvergenceException - Exception in com.imsl.math
Corrector failed to converge.
FeynmanKac.CorrectorConvergenceException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.CorrectorConvergenceException
Corrector failed to converge.
FeynmanKac.ErrorTestException - Exception in com.imsl.math
Error test failure detected.
FeynmanKac.ErrorTestException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.ErrorTestException
Error test failure detected.
FeynmanKac.ForcingTerm - Interface in com.imsl.math
Public interface for non-zero forcing term in the Feynman-Kac equation.
FeynmanKac.InitialConstraintsException - Exception in com.imsl.math
The constraints at the initial point are inconsistent.
FeynmanKac.InitialConstraintsException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.InitialConstraintsException
The constraints at the initial point are inconsistent.
FeynmanKac.InitialData - Interface in com.imsl.math
Public interface for adjustment of initial data or as an opportunity for output during the integration steps.
FeynmanKac.IterationMatrixSingularException - Exception in com.imsl.math
Iteration matrix is singular.
FeynmanKac.IterationMatrixSingularException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.IterationMatrixSingularException
Iteration matrix is singular.
FeynmanKac.PdeCoefficients - Interface in com.imsl.math
Public interface for user supplied PDE coefficients in the Feynman-Kac PDE.
FeynmanKac.TcurrentTstopInconsistentException - Exception in com.imsl.math
The end value for the integration in time, tout, is not consistent with the current time value, t.
FeynmanKac.TcurrentTstopInconsistentException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.TcurrentTstopInconsistentException
The end value for the integration in time, tout, is not consistent with the current time value, t.
FeynmanKac.TEqualsToutException - Exception in com.imsl.math
The current integration point in time and the end point are equal.
FeynmanKac.TEqualsToutException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.TEqualsToutException
The current integration point in time and the end point are equal.
FeynmanKac.TimeIntervalTooSmallException - Exception in com.imsl.math
Distance between starting time point and end point for the integration is too small.
FeynmanKac.TimeIntervalTooSmallException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.TimeIntervalTooSmallException
Distance between starting time point and end point for the integration is too small.
FeynmanKac.ToleranceTooSmallException - Exception in com.imsl.math
Tolerance is too small.
FeynmanKac.ToleranceTooSmallException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.ToleranceTooSmallException
Tolerance is too small.
FeynmanKac.TooManyIterationsException - Exception in com.imsl.math
Too many iterations required by the DAE solver.
FeynmanKac.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.TooManyIterationsException
Too many iterations required by the DAE solver.
FFT - Class in com.imsl.math
FFT functions.
FFT(int) - Constructor for class com.imsl.math.FFT
Constructs an FFT object.
FILL - Static variable in class com.imsl.chart.Draw
 
FILL_FACTOR - Static variable in class com.imsl.math.ComplexSuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
FILL_FACTOR - Static variable in class com.imsl.math.SuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
FILL_TYPE_GRADIENT - Static variable in class com.imsl.chart.ChartNode
Value for attribute "FillType" indicating that the region is to be drawn in a color gradient as specified by the attribute Gradient.
FILL_TYPE_NONE - Static variable in class com.imsl.chart.ChartNode
Value for attribute "FillType" and "FillOutlineType" indicating that the region is not to be drawn.
FILL_TYPE_PAINT - Static variable in class com.imsl.chart.ChartNode
Value for attribute "FillType" indicating that the region is to be drawn using the texture specified by the attribute FillPaint.
FILL_TYPE_SOLID - Static variable in class com.imsl.chart.ChartNode
Value for attribute "FillType" and "FillOutlineType" indicating that the region is to be drawn using the solid color specified by the attribute FillColor or FillOutlineColor.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.Draw
Fills a circular or elliptical arc covering the specified rectangle.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawMap
Fills a circular or elliptical arc covering the specified rectangle.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawPick
Fills a circular or elliptical arc covering the specified rectangle.
fillColor - Variable in class com.imsl.chart.Draw
 
fillOutlineColor - Variable in class com.imsl.chart.Draw
 
fillOutlineType - Variable in class com.imsl.chart.Draw
 
fillPaint - Variable in class com.imsl.chart.Draw
 
FillPaint - Class in com.imsl.chart
A collection of methods to create Paint objects for fill areas.
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.Draw
Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.Draw
Fill a polygon defined by a Polygon object.
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.DrawMap
Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.DrawMap
Fill a polygon defined by a Polygon object.
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.DrawPick
Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.DrawPick
Fill a polygon defined by a Polygon object.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.Draw
Fill a rectangle.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.DrawMap
Fill a rectangle.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.DrawPick
Fill a rectangle.
fillType - Variable in class com.imsl.chart.Draw
 
filter() - Method in class com.imsl.stat.KalmanFilter
Performs Kalman filtering and evaluates the likelihood function for the state-space model.
finalize() - Method in class com.imsl.chart.Chart
 
finalize() - Method in class com.imsl.chart3d.Chart3D
 
Finance - Class in com.imsl.finance
Collection of finance functions.
findColumn(String) - Method in class com.imsl.io.AbstractFlatFile
Maps the given ResultSet column name to its ResultSet column index.
findColumnName(int) - Method in class com.imsl.io.AbstractFlatFile
Maps the given columnIndex into its column name.
findLink(Node, Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the Link between two Nodes.
findLinks(Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns all of the Links to a given Node.
finite(double) - Static method in class com.imsl.math.IEEE
Finite number test on an argument of type double.
fire() - Method in class com.imsl.chart.DrawPick
Fires the pickListeners for all of the picked nodes.
firePickListeners(MouseEvent) - Method in class com.imsl.chart.ChartNode
Fires the pick listeners defined at this node and at all of its ancestors, if the event "hits" the node.
first() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the first row in this ResultSet object.
FIRST - Static variable in class com.imsl.stat.TimeSeriesOperations.CombineMethod
Uses the value from ts1, the first series in the call.
FIRST_DERIVATIVE - Static variable in class com.imsl.math.CsInterpolate
 
FIRST_GRAM_SCHMIDT - Static variable in class com.imsl.math.GenMinRes
Indicates the first Gram-Schmidt implementation method is to be used.
FIRST_HOUSEHOLDER - Static variable in class com.imsl.math.GenMinRes
Indicates the first Householder implementation method is to be used.
fitModel() - Method in class com.imsl.datamining.decisionTree.DecisionTree
Fits the decision tree.
fitModel() - Method in class com.imsl.datamining.GradientBoosting
Performs the gradient boosting on the training data.
fitModel() - Method in class com.imsl.datamining.PredictiveModel
Fits the predictive model to the training data (estimates the model using the training data and current configuration settings).
FlatFile - Class in com.imsl.io
Reads a text file as a ResultSet.
FlatFile(BufferedReader, Tokenizer) - Constructor for class com.imsl.io.FlatFile
Creates a FlatFile from a BufferedReader.
FlatFile(BufferedReader) - Constructor for class com.imsl.io.FlatFile
Creates a FlatFile with the CSV tokenizer.
FlatFile(String) - Constructor for class com.imsl.io.FlatFile
Creates a FlatFile from a CSV file.
FlatFile(String, Tokenizer) - Constructor for class com.imsl.io.FlatFile
Creates a FlatFile from a file.
FlatFile.Parser - Interface in com.imsl.io
Defines a method that parses a String into an Object.
floatValue() - Method in class com.imsl.math.Complex
Returns the value of the real part as a float.
floatValue() - Method in class com.imsl.math.Physical
Returns the value of this dimensionless object.
floor(double) - Static method in class com.imsl.math.JMath
Returns the value of a double rounded toward negative infinity to an integral value.
force(int, double[], double, double, double[], double[], double[][], double[], double[][]) - Method in interface com.imsl.math.FeynmanKac.ForcingTerm
Computes approximations to the forcing term phi(f,x,t) and its derivative partial phi/partial y.
forecast(double[]) - Method in class com.imsl.datamining.KohonenSOM
Returns a forecast computed using the KohonenSOM object.
forecast(double[][]) - Method in class com.imsl.datamining.KohonenSOM
Returns forecasts computed using the KohonenSOM object.
forecast(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Computes a forecast using the Network.
forecast(double[]) - Method in class com.imsl.datamining.neural.Network
Returns a forecast for each of the Network's outputs computed from the trained Network.
forecast(int) - Method in class com.imsl.stat.ARAutoUnivariate
Returns forecasts and associated confidence interval offsets.
forecast(int) - Method in class com.imsl.stat.ARMA
Computes forecasts and their associated probability limits for an ARMA model.
forecast(int) - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns forecasts for lead times l=1,2,ldots,rm{nForecast} at origins z.length-backwardOrigin-1+j where j=1,ldots,rm{backwardOrigin}+1.
forecast(int) - Method in class com.imsl.stat.AutoARIMA
Computes forecasts, associated probability limits and psi weights for the given outlier contaminated time series.
format(LogRecord) - Method in class com.imsl.IMSLFormatter
Format the given log record and return the formatted string.
format(int, Object, int, int, ParsePosition) - Method in class com.imsl.math.PrintMatrixFormat
Returns a formatted string.
formatLabel(double, double) - Method in class com.imsl.chart.Data
 
formatMessage(String, String, Object[]) - Static method in class com.imsl.Messages
A message is formatted using a MessageFormat string retrieved from the named resource bundle using the given key.
formatMessage(String, String) - Static method in class com.imsl.Messages
A message is formatted, without arguments, using a MessageFormat string retrieved from the named resource bundle using the given key.
forward(Complex[]) - Method in class com.imsl.math.ComplexFFT
Compute the Fourier coefficients of a complex periodic sequence.
forward(double[]) - Method in class com.imsl.math.FFT
Compute the Fourier coefficients of a real periodic sequence.
FORWARD_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression
Indicates forward regression.
frobeniusNorm(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Return the Frobenius norm of a Complex matrix.
frobeniusNorm() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the Frobenius norm of the matrix.
frobeniusNorm(double[][]) - Static method in class com.imsl.math.Matrix
Return the Frobenius norm of a matrix.
frobeniusNorm() - Method in class com.imsl.math.SparseMatrix
Returns the Frobenius norm of the matrix.
FULL - Static variable in class com.imsl.math.PrintMatrix
This flag as the argument to setMatrixType, indicates that the full matrix is to be printed.
fv(double, int, double, double, int) - Static method in class com.imsl.finance.Finance
Returns the future value of an investment.
fvschedule(double, double[]) - Static method in class com.imsl.finance.Finance
Returns the future value of an initial principal taking into consideration a schedule of compound interest rates.

G

g(double) - Method in interface com.imsl.datamining.neural.Activation
Returns the value of the activation function.
g(double) - Method in interface com.imsl.math.MinUncon.Derivative
Public interface for the smooth function of a single variable to be minimized.
g(double) - Method in interface com.imsl.math.RadialBasis.Function
The derivative of the radial basis function used to calculate the gradient of the radial basis approximation.
g(double) - Method in class com.imsl.math.RadialBasis.Gaussian
The derivative of the Gaussian basis function used to calculate the gradient of the radial basis approximation.
g(double) - Method in class com.imsl.math.RadialBasis.HardyMultiquadric
The derivative of the Hardy multiquadric basis function used to calculate the gradient of the radial basis approximation.
gamma(double) - Static method in class com.imsl.math.Sfun
Returns the Gamma function of a double.
gamma(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the gamma cumulative probability distribution function.
gamma(double, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the gamma cumulative probability distribution function.
gamma(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the gamma probability density function.
GammaDistribution - Class in com.imsl.stat
Evaluates a gamma probability density for a given set of data.
GammaDistribution() - Constructor for class com.imsl.stat.GammaDistribution
 
gammaIncomplete(double, double) - Static method in class com.imsl.math.Sfun
Evaluates the incomplete gamma function.
GammaPD - Class in com.imsl.stat.distributions
The gamma probability distribution
GammaPD() - Constructor for class com.imsl.stat.distributions.GammaPD
Constructor for the gamma probability distribution
GARCH - Class in com.imsl.stat
Computes estimates of the parameters of a GARCH(p,q) model.
GARCH(int, int, double[], double[]) - Constructor for class com.imsl.stat.GARCH
Constructor for GARCH.
GARCH.ConstrInconsistentException - Exception in com.imsl.stat
The equality constraints are inconsistent.
GARCH.ConstrInconsistentException(String) - Constructor for exception com.imsl.stat.GARCH.ConstrInconsistentException
Constructs a ConstrInconsistentException object.
GARCH.ConstrInconsistentException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.ConstrInconsistentException
Constructs a ConstrInconsistentException object.
GARCH.EqConstrInconsistentException - Exception in com.imsl.stat
The equality constraints and the bounds on the variables are found to be inconsistent.
GARCH.EqConstrInconsistentException(String) - Constructor for exception com.imsl.stat.GARCH.EqConstrInconsistentException
Constructs a EqConstrInconsistentException object.
GARCH.EqConstrInconsistentException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.EqConstrInconsistentException
Constructs a EqConstrInconsistentException object.
GARCH.NoVectorXException - Exception in com.imsl.stat
No vector X satisfies all of the constraints.
GARCH.NoVectorXException(String) - Constructor for exception com.imsl.stat.GARCH.NoVectorXException
Constructs a NoVectorXException object.
GARCH.NoVectorXException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.NoVectorXException
Constructs a NoVectorXException object.
GARCH.TooManyIterationsException - Exception in com.imsl.stat
Number of function evaluations exceeded 1000.
GARCH.TooManyIterationsException(String) - Constructor for exception com.imsl.stat.GARCH.TooManyIterationsException
Constructs a TooManyIterationsException object.
GARCH.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.TooManyIterationsException
Constructs a TooManyIterationsException object.
GARCH.VarsDeterminedException - Exception in com.imsl.stat
The variables are determined by the equality constraints.
GARCH.VarsDeterminedException(String) - Constructor for exception com.imsl.stat.GARCH.VarsDeterminedException
Constructs a VarsDeterminedException object.
GARCH.VarsDeterminedException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.VarsDeterminedException
Constructs a VarsDeterminedException object.
GENERALIZED_LEAST_SQUARES - Static variable in class com.imsl.stat.FactorAnalysis
Indicates generalized least squares method.
GenMinRes - Class in com.imsl.math
Linear system solver using the restarted Generalized Minimum Residual (GMRES) method.
GenMinRes(int, GenMinRes.Function) - Constructor for class com.imsl.math.GenMinRes
GMRES linear system solver constructor.
GenMinRes.Function - Interface in com.imsl.math
Public interface for the user supplied function to GenMinRes.
GenMinRes.Norm - Interface in com.imsl.math
Public interface for the user supplied function to the GenMinRes object used for the norm Vert X Vert when the Gram-Schmidt implementation is used.
GenMinRes.Preconditioner - Interface in com.imsl.math
Public interface for the user supplied function to GenMinRes used for preconditioning.
GenMinRes.TooManyIterationsException - Exception in com.imsl.math
Maximum number of iterations exceeded.
GenMinRes.TooManyIterationsException(String) - Constructor for exception com.imsl.math.GenMinRes.TooManyIterationsException
Constructs a TooManyIterationsException object.
GenMinRes.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.math.GenMinRes.TooManyIterationsException
Constructs a TooManyIterationsException object.
GenMinRes.VectorProducts - Interface in com.imsl.math
Public interface for the user supplied function to the GenMinRes object used for the inner product when the Gram-Schmidt implementation is used.
geometric(int, double) - Static method in class com.imsl.stat.Cdf
Evaluates the discrete geometric cumulative probability distribution function.
geometric(double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the discrete geometric cumulative probability distribution function.
geometric(int, double) - Static method in class com.imsl.stat.Pdf
Evaluates the discrete geometric probability density function.
get(String) - Method in class com.imsl.chart.xml.ChartXML
Returns a generated object given the id attribute in the XML tag that created the object.
get(int, int) - Method in class com.imsl.math.ComplexSparseMatrix
Returns the value of an element in the matrix.
get(int, int) - Method in class com.imsl.math.SparseMatrix
Returns the value of an element in the matrix.
getAbsoluteErrorTolerances() - Method in class com.imsl.math.FeynmanKac
Returns absolute error tolerances.
getAbsoluteH() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the value for H used for setting limits.
getAbstractParent() - Method in class com.imsl.chart.AbstractChartNode
Returns the parent of this node.
getActivation() - Method in class com.imsl.datamining.neural.Perceptron
Returns the activation function.
getAdjustedANOVA() - Method in class com.imsl.stat.ANCOVA
Returns the partial sum of squares for the one-way analysis of covariance.
getAdjustedRSquared() - Method in class com.imsl.stat.ANOVA
Returns the adjusted R-squared (in percent).
getAIC() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final estimate for Akaike's Information Criterion (AIC) at the optimum.
getAIC() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns Akaike's information criterion (AIC).
getAIC() - Method in class com.imsl.stat.ARSeasonalFit
Returns the final estimate for Akaike's Information Criterion (AIC) at the optimum.
getAIC() - Method in class com.imsl.stat.AutoARIMA
Returns Akaike's information criterion (AIC) for the optimum model.
getAICC() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns Akaike's Corrected Information Criterion (AICC).
getAICC() - Method in class com.imsl.stat.AutoARIMA
Returns Akaike's Corrected Information Criterion (AICC) for the optimum model.
getAkaike() - Method in class com.imsl.stat.GARCH
Returns the value of Akaike Information Criterion evaluated at the estimated parameter array.
getAlignment() - Method in class com.imsl.chart.Text
Gets the alignment for this Text object.
getALT() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ALT" attribute.
getALT() - Method in class com.imsl.chart.DrawMap
Returns the current ALT string.
getANCOVA() - Method in class com.imsl.stat.ANCOVA
Returns an array containing the one-way analysis of covariance assuming parallelism.
getANOVA() - Method in class com.imsl.math.RadialBasis
Returns the ANOVA statistics from the linear regression.
getANOVA() - Method in class com.imsl.stat.LinearRegression
Get an analysis of variance table and related statistics.
getANOVA() - Method in class com.imsl.stat.StepwiseRegression
Get an analysis of variance table and related statistics.
getANOVA() - Method in class com.imsl.stat.UserBasisRegression
Get an analysis of variance table and related statistics.
getANOVATable() - Method in class com.imsl.stat.ANOVAFactorial
Returns the analysis of variance table.
getANOVATables() - Method in class com.imsl.stat.ANCOVA
Returns a matrix of size ngroup by 15 containing the analysis of variance tables for each linear regression model fitted separately to each treatment group.
getAR() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final auto regressive parameter estimates at the optimum AIC using the estimation method specified in setEstimationMethod .
getAR() - Method in class com.imsl.stat.ARMA
Returns the final autoregressive parameter estimates.
getAR() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the final autoregressive parameter estimates.
getAR() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the final autoregressive parameter estimates.
getAR() - Method in class com.imsl.stat.ARSeasonalFit
Returns the final autoregressive parameter estimates at the optimum in the transformed series W_t.
getAR() - Method in class com.imsl.stat.AutoARIMA
Returns the final autoregressive parameter estimates of the optimum model.
getARCH() - Method in class com.imsl.stat.GARCH
Returns the estimated values of the ARCH coefficients.
getARConstants() - Method in class com.imsl.stat.VectorAutoregression
Returns the current settings of the constants used in the autoregression model.
getARModel() - Method in class com.imsl.stat.VectorAutoregression
Returns the autoregressive model configuration.
getAROrder() - Method in class com.imsl.stat.ARSeasonalFit
Returns optimum number of lags, p, for the optimum autoregressive AR(p) model.
getArray(String) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as an Array object in the Java programming language.
getArray() - Method in class com.imsl.stat.ANOVA
Returns the ANOVA values as an array.
getAsciiStream(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a stream of ASCII characters.
getAsciiStream(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a stream of ASCII characters.
getAssociationRules(Itemsets, double, double) - Static method in class com.imsl.datamining.Apriori
Returns strong association rules among the itemsets in itemsets.
getAttribute(String) - Method in class com.imsl.chart.AbstractChartNode
Gets an attribute.
getAutoCorrelations() - Method in class com.imsl.stat.AutoCorrelation
Returns the autocorrelations of the time series x.
getAutoCorrelationX() - Method in class com.imsl.stat.CrossCorrelation
Returns the autocorrelations of the time series x.
getAutoCorrelationY() - Method in class com.imsl.stat.CrossCorrelation
Returns the autocorrelations of the time series y.
getAutoCovariance() - Method in class com.imsl.stat.ARMA
Returns the autocovariances of the time series z.
getAutoCovariances() - Method in class com.imsl.stat.AutoCorrelation
Returns the variance and autocovariances of the time series x.
getAutoCovarianceX() - Method in class com.imsl.stat.CrossCorrelation
Returns the autocovariances of the time series x.
getAutoCovarianceY() - Method in class com.imsl.stat.CrossCorrelation
Returns the autocovariances of the time series y.
getAutoscaleInput() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "AutoscaleInput" attribute.
getAutoscaleMinimumTimeInterval() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "AutoscaleMinimumTimeInterval" attribute.
getAutoscaleOutput() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "AutoscaleOutput" attribute.
getAxis() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Axis" attribute.
getAxisBox() - Method in class com.imsl.chart3d.AxisXYZ
Return the axis box node.
getAxisLabel() - Method in class com.imsl.chart.Axis1D
Returns the label node associated with this axis.
getAxisLabel() - Method in class com.imsl.chart3d.Axis3D
Returns the label node associated with this axis.
getAxisLine() - Method in class com.imsl.chart.Axis1D
Returns the axis line node associated with this axis.
getAxisLine() - Method in class com.imsl.chart3d.Axis3D
Returns the axis line node associated with this axis.
getAxisR() - Method in class com.imsl.chart.Polar
Return the radius axis node.
getAxisRLabel() - Method in class com.imsl.chart.AxisR
Returns the AxisRLabel node.
getAxisRLine() - Method in class com.imsl.chart.AxisR
Returns the AxisRLine node.
getAxisRMajorTick() - Method in class com.imsl.chart.AxisR
Returns the major tick node associated with this axis.
getAxisTheta() - Method in class com.imsl.chart.Polar
Return the angular axis node.
getAxisTitle() - Method in class com.imsl.chart.Axis1D
Returns the title node associated with this axis.
getAxisTitle() - Method in class com.imsl.chart3d.Axis3D
Returns the title node associated with this axis.
getAxisTitlePosition() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "AxisTitlePosition" attribute.
getAxisUnit() - Method in class com.imsl.chart.Axis1D
Returns the unit node associated with this axis.
getAxisX() - Method in class com.imsl.chart.AxisXY
Return the x-axis node.
getAxisX() - Method in class com.imsl.chart3d.AxisXYZ
Return the x-axis node.
getAxisY() - Method in class com.imsl.chart.AxisXY
Return the y-axis node.
getAxisY() - Method in class com.imsl.chart3d.AxisXYZ
Return the y-axis node.
getAxisZ() - Method in class com.imsl.chart3d.AxisXYZ
Return the z-axis node.
getBackground() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Background" attribute.
getBackground() - Method in class com.imsl.chart3d.Chart3D
Returns the value of the "Background" attribute.
getBackwardOrigin() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the maximum backward origin.
getBackwardOrigin() - Method in class com.imsl.stat.ARMA
Returns the user-specified backward origin
getBackwardOrigin() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the current value for forecasting backward origin.
getBalancedTable() - Method in class com.imsl.stat.TableMultiWay
Returns an object containing the balanced table.
getBarData() - Method in class com.imsl.chart.Bar
Returns the "BarData" attribute.
getBarGap() - Method in class com.imsl.chart.ChartNode
Returns the value of the "BarGap" attribute.
getBarItem() - Method in class com.imsl.chart.BarSet
Returns an array of BarItems.
getBarItem(int) - Method in class com.imsl.chart.BarSet
Returns the BarItem given the index.
getBarMinus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the value of the attribute "BarMinus" containing the C^{-} bars.
getBarPlus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the value of the attribute "BarPlus" containing the C^{+} bars.
getBarSet() - Method in class com.imsl.chart.Bar
Returns the BarSet object.
getBarSet(int, int) - Method in class com.imsl.chart.Bar
Returns the BarSet object.
getBarSet(int) - Method in class com.imsl.chart.Bar
Returns the BarSet object.
getBarType() - Method in class com.imsl.chart.ChartNode
Returns the value of the "BarType" attribute.
getBarWidth() - Method in class com.imsl.chart.ChartNode
Returns the value of the "BarWidth" attribute.
getBase() - Method in class com.imsl.stat.FaureSequence
Returns the base.
getBias() - Method in class com.imsl.datamining.neural.Perceptron
Returns the bias for this Perceptron.
getBIC() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the Bayesian Information Criterion (BIC).
getBIC() - Method in class com.imsl.stat.AutoARIMA
Returns the Bayesian Information Criterion (BIC) for the optimum model.
getBigDecimal(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.math.BigDecimal with full precision.
getBigDecimal(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.math.BigDecimal with full precision.
getBinaryStream(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a binary stream of uninterpreted bytes.
getBinaryStream(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a stream of uninterpreted bytes.
getBlob(int) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Blob object in the Java programming language.
getBlob(String) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Blob object in the Java programming language.
getBlomScores(double[]) - Method in class com.imsl.stat.Ranks
Gets the Blom version of normal scores for each observation.
getBodies() - Method in class com.imsl.chart.BoxPlot
Returns a node containing the body elements in the Box plot.
getBoolean(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a boolean in the Java programming language.
getBoolean(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a boolean in the Java programming language.
getBooleanAttribute(String, boolean) - Method in class com.imsl.chart.AbstractChartNode
Convenience routine to get a Boolean-valued attribute.
getBoundingSphere() - Method in class com.imsl.chart3d.ChartNode3D
Gets the spherical bounding region object BoundingSphere.
getBounds() - Method in class com.imsl.datamining.neural.ScaleFilter
Retrieves bounds used during bounded scaling.
getBoxPlotType() - Method in class com.imsl.chart.BoxPlot
Returns the value of the "BoxPlotType" attribute.
getBreakpoints() - Method in class com.imsl.math.Spline
Returns a copy of the breakpoints.
getByte(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a byte in the Java programming language.
getByte(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a byte in the Java programming language.
getBytes(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a byte array in the Java programming language.
getBytes(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a byte array in the Java programming language.
getCanvas() - Method in class com.imsl.chart3d.Chart3D
 
getCanvas() - Method in class com.imsl.chart3d.JFrameChart3D
Returns the Canvas3DChart into which the chart is drawn.
getCaseAnalysis() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the case analysis.
getCaseStatistics(double[], double) - Method in class com.imsl.stat.LinearRegression
Returns the case statistics for an observation.
getCaseStatistics(double[], double, double) - Method in class com.imsl.stat.LinearRegression
Returns the case statistics for an observation and a weight.
getCaseStatistics(double[], double, int) - Method in class com.imsl.stat.LinearRegression
Returns the case statistics for an observation and future response count for the desired prediction interval.
getCaseStatistics(double[], double, double, int) - Method in class com.imsl.stat.LinearRegression
Returns the case statistics for an observation, weight, and future response count for the desired prediction interval.
getCaseStatistics() - Method in class com.imsl.stat.ProportionalHazards
Returns the case statistics for each observation.
getCellCounts() - Method in class com.imsl.stat.ChiSquaredTest
Returns the cell counts.
getCensorColumn() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the column index of x containing the optional censoring code for each observation.
getCensorColumn() - Method in class com.imsl.stat.ProportionalHazards
Returns the column index of x containing the optional censoring code for each observation.
getCenter() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the value of the attribute "Center".
getCenter() - Method in class com.imsl.datamining.neural.ScaleFilter
Retrieves the measure of center to be used during z-score scaling.
getCenter() - Method in class com.imsl.stat.ARSeasonalFit
Returns the current setting for centering the input time series.
getCenterLine() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the center line.
getCharacterStream(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.
getCharacterStream(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.
getChart() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Chart" attribute.
getChart(HttpServletRequest) - Method in class com.imsl.chart.ChartServlet
Returns the chart found in the session saved with the key "chart"+id, where id is the value of the "id" parameter in the request.
getChart() - Method in class com.imsl.chart.JFrameChart
Return the Chart object.
getChart() - Method in class com.imsl.chart.JPanelChart
Return the Chart object.
getChart() - Method in class com.imsl.chart.xml.ChartXML
Returns the root node of the chart tree.
getChart3D() - Method in class com.imsl.chart3d.Canvas3DChart
Returns the Chart3D associated with this canvas.
getChart3D() - Method in class com.imsl.chart3d.JFrameChart3D
Return the Chart object.
getChartServletName() - Method in class com.imsl.chart.JspBean
Returns the URL of the servlet used to render the chart.
getChartTitle() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ChartTitle" attribute.
getChildId(int) - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the id of a child node.
getChildList() - Method in class com.imsl.chart.AbstractChartNode
Returns the children of this node.
getChildren() - Method in class com.imsl.chart.ChartNode
Returns an array of the children of this node.
getChildren() - Method in class com.imsl.chart3d.ChartNode3D
Returns an array of the children of this node.
getChildrenIds() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the array of child node id's.
getChiSquared() - Method in class com.imsl.stat.ChiSquaredTest
Returns the chi-squared statistic.
getChiSquared() - Method in class com.imsl.stat.ContingencyTable
Returns the Pearson chi-squared test statistic.
getChiSquared() - Method in class com.imsl.stat.NormalityTest
Returns the chi-square statistic for the chi-squared goodness-of-fit test.
getChiSquaredTest() - Method in class com.imsl.stat.NormOneSample
Returns the test statistic associated with the chi-squared test for variances.
getChiSquaredTest() - Method in class com.imsl.stat.NormTwoSample
Returns the test statistic associated with the chi-squared test for common, or pooled, variances.
getChiSquaredTestDF() - Method in class com.imsl.stat.NormOneSample
Returns the degrees of freedom associated with the chi-squared test for variances.
getChiSquaredTestDF() - Method in class com.imsl.stat.NormTwoSample
Returns the degrees of freedom associated with the chi-squared test for the common, or pooled, variances.
getChiSquaredTestP() - Method in class com.imsl.stat.NormOneSample
Returns the probability of a larger chi-squared associated with the chi-squared test for variances.
getChiSquaredTestP() - Method in class com.imsl.stat.NormTwoSample
Returns the probability of a larger chi-squared associated with the chi-squared test for common, or pooled, variances.
getClassCounts(int[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns the number of patterns for each target classification.
getClassCounts() - Method in class com.imsl.datamining.PredictiveModel
Returns the counts of each class (level) of the categorical response variable.
getClassFittedValues() - Method in class com.imsl.datamining.GradientBoosting
Returns the fitted values {f(x_i)} for a categorical response variable with two or more levels.
getClassificationErrors() - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns the classification probability errors for each pattern in the training data.
getClassificationVariableCounts() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the number of values taken by each classification variable.
getClassificationVariableValues() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the distinct values of the classification variables in ascending order.
getClassMembership() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the group number to which the observation was classified.
getClassProbabilities() - Method in class com.imsl.datamining.GradientBoosting
Returns the predicted probabilities on the training data for a categorical response variable.
getClassTable() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the classification table.
getClassValueCounts() - Method in class com.imsl.stat.ProportionalHazards
Returns the number of values taken by each classification variable.
getClassValues() - Method in class com.imsl.stat.ProportionalHazards
Returns the class values taken by each classification variable.
getClipBounds() - Method in class com.imsl.chart.Draw
Get the clipping rectangle.
getClipData() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ClipData" attribute.
getClob(int) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Clob object in the Java programming language.
getClob(String) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Clob object in the Java programming language.
getClose() - Method in class com.imsl.chart.HighLowClose
Gets the value of the attribute "Close".
getClosedFormMLE(double[]) - Method in interface com.imsl.stat.distributions.ClosedFormMaximumLikelihoodInterface
Returns the maximum likelihood estimates (MLEs).
getClosedFormMlStandardError(double[]) - Method in interface com.imsl.stat.distributions.ClosedFormMaximumLikelihoodInterface
Returns the standard error based on the closed form solution of the maximum liklihood for the sample data.
getClusterCounts() - Method in class com.imsl.stat.ClusterKMeans
Returns the number of observations in each cluster.
getClusterLeftSons() - Method in class com.imsl.stat.ClusterHierarchical
Returns the left sons of each merged cluster.
getClusterLevel() - Method in class com.imsl.stat.ClusterHierarchical
Returns the level at which the clusters are joined.
getClusterMembership(int) - Method in class com.imsl.stat.ClusterHierarchical
Returns the cluster membership of each observation.
getClusterMembership() - Method in class com.imsl.stat.ClusterKMeans
Returns the cluster membership for each observation.
getClusterRightSons() - Method in class com.imsl.stat.ClusterHierarchical
Returns the right sons of each merged cluster.
getClusterSSQ() - Method in class com.imsl.stat.ClusterKMeans
Returns the within sum of squares for each cluster.
getCMinus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the C^{-} values.
getCoefficient(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests
Returns the estimate for a coefficient.
getCoefficient(int) - Method in class com.imsl.stat.NonlinearRegression
Returns the estimate for a coefficient.
getCoefficient(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests
Returns the estimate for a coefficient of the independent variable.
getCoefficientOfVariation() - Method in class com.imsl.stat.ANOVA
Returns the coefficient of variation (in percent).
getCoefficients() - Method in class com.imsl.io.MPSReader.Row
Returns the coeffients of this row as a dense array.
getCoefficients() - Method in class com.imsl.math.Spline2D
Returns the coefficients for the tensor-product spline.
getCoefficients() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the linear discriminant function coefficients.
getCoefficients() - Method in class com.imsl.stat.LinearRegression
Returns the regression coefficients.
getCoefficients() - Method in class com.imsl.stat.NonlinearRegression
Returns the regression coefficients.
getCoefficients() - Method in class com.imsl.stat.UserBasisRegression
Returns the regression coefficients.
getCoefficientStatistics(int) - Method in class com.imsl.stat.SelectionRegression.Statistics
Returns the coefficients statistics for each of the best regressions found for each subset considered.
getCoefficientTable(int) - Method in class com.imsl.stat.ANCOVA
Returns a matrix of size ncov + 1 by 4 containing statistics for a linear regression model fitted separately for each of the ngroup treatment groups.
getCoefficientTables() - Method in class com.imsl.stat.ANCOVA
Returns an array containing statistics for a linear regression model fitted separately for all ngroup treatments.
getCoefficientTTests() - Method in class com.imsl.stat.LinearRegression
Returns statistics relating to the regression coefficients.
getCoefficientTTests() - Method in class com.imsl.stat.StepwiseRegression
Returns the student-t test statistics for the regression coefficients.
getCoefficientVIF() - Method in class com.imsl.stat.StepwiseRegression
Returns the variance inflation factors for the final model in this invocation.
getColorAttribute(String) - Method in class com.imsl.chart.AbstractChartNode
Convenience routine to get a Color-valued attribute.
getColorFunction() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "ColorFunction" attribute.
getColormap() - Method in class com.imsl.chart.Heatmap
Returns the value of the "Colormap" attribute.
getColormap() - Method in class com.imsl.chart.Treemap
Returns the value of the "Colormap" attribute.
getColumn() - Method in class com.imsl.io.MPSReader.Element
Returns the column index.
getColumnClass(int) - Method in class com.imsl.io.AbstractFlatFile
Returns the class of the items in the specified column.
getColumnCount() - Method in class com.imsl.io.AbstractFlatFile
Returns the number of columns in this ResultSet object.
getColumnCount() - Method in class com.imsl.io.FlatFile
Returns the number of columns in this ResultSet object.
getColumnPermutationMethod() - Method in class com.imsl.math.ComplexSuperLU
Returns the method that will be used to permute the columns of the input matrix.
getColumnPermutationMethod() - Method in class com.imsl.math.SuperLU
Returns the method that will be used to permute the columns of the input matrix.
getCompleteTimes() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns an int array of all time points, including values for times with missing values in z.
getCompleteTimes() - Method in class com.imsl.stat.AutoARIMA
Returns all time points at which the original series was observed, including values for times with missing values in x.
getCompleteTimeSeries() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns a double precision vector of length tpoints[tpoints.length-1]-tpoints[0]+1 containing the observed values in the time series z plus estimates for missing values in gaps identified in tpoints.
getCompleteTimeSeries() - Method in class com.imsl.stat.AutoARIMA
Returns the original series with potentially missing values replaced by estimates.
getComponent() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Component" attribute.
getConcatenatedViewport() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Viewport" attribute concatenated with the "Viewport" attributes set in its ancestor nodes.
getConcatenatedViewport() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Viewport" attribute concatenated with the "Viewport" attributes set in its ancestor nodes.
getConcurrency() - Method in class com.imsl.io.AbstractFlatFile
Returns the concurrency mode of this ResultSet object.
getConditionNumber() - Method in class com.imsl.math.ComplexSuperLU
Returns the estimate of the reciprocal condition number of the matrix A.
getConditionNumber() - Method in class com.imsl.math.SuperLU
Returns the estimate of the reciprocal condition number of the matrix A.
getConfidence() - Method in class com.imsl.datamining.AssociationRule
The confidence measure of the association rule.
getConfidence() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the confidence level for calculating confidence limit deviations returned from getDeviations.
getConfidence() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the confidence level used for calculating deviations in getDeviations.
getConfidenceInterval(double, int, int, int) - Method in class com.imsl.stat.ANOVA
Computes the confidence interval associated with the difference of means between two groups using a specified method.
getConfidenceInterval() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Confidence Interval of the population mean for an observation.
getConstant() - Method in class com.imsl.math.SparseLP
Returns the value of the constant term in the objective function.
getConstant() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the estimate for the constant parameter in the ARMA series.
getConstant() - Method in class com.imsl.stat.ARMA
Returns the constant parameter estimate.
getConstant() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the estimate for the constant parameter in the ARMA series.
getConstant() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the constant parameter estimate.
getConstant() - Method in class com.imsl.stat.AutoARIMA
Returns the constant parameter estimate for the optimum model.
getConstantColumn() - Method in class com.imsl.stat.ProportionalHazards
Returns the column index of x containing the constant to be added to the linear response.
getConstraintResiduals() - Method in class com.imsl.math.MinConNLP
Returns the constraint residuals.
getConstraintType() - Method in class com.imsl.math.SparseLP
Returns the types of general constraints in the matrix A.
getContingencyCoef() - Method in class com.imsl.stat.ContingencyTable
Returns contingency coefficient.
getContourLegend() - Method in class com.imsl.chart.Contour
Returns the contour chart legend.
getContourLevel() - Method in class com.imsl.chart.Contour
Returns all of the contour levels.
getContourLevel(int) - Method in class com.imsl.chart.Contour
Returns a ContourLevel.
getContributions() - Method in class com.imsl.stat.ContingencyTable
Returns the contributions to chi-squared for each cell in the table.
getControlData() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the Data object for the control data.
getControlLimit() - Method in class com.imsl.chart.qc.ControlLimit
Returns the value of the attribute "ControlLimit".
getConvergenceTol() - Method in class com.imsl.stat.ProportionalHazards
Returns the convergence tolerance used.
getConvergenceTolerance() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the tolerance level used to determine convergence of the nonlinearleast-squares and maximum likelihood algorithms.
getConvergenceTolerance() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the current value of convergence tolerance used by the AR_1 and AR_P estimation methods.
getCooksDistance() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns Cook's Distance for an observation.
getCoordinates() - Method in class com.imsl.chart.Dendrogram
Convenience routine to get the "Coordinates" attribute.
getCorrelations() - Method in class com.imsl.stat.FactorAnalysis
Returns the correlations of the principal components.
getCost() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the misclassification cost of a node (in-sample cost measure at the current node).
getCostComplexityValues() - Method in class com.imsl.datamining.decisionTree.DecisionTree
Returns an array containing cost-complexity values.
getCostMatrix() - Method in class com.imsl.datamining.PredictiveModel
Returns the cost matrix for a categorical response variable.
getCount() - Method in class com.imsl.stat.FaureSequence
 
getCovariance() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the array of covariances.
getCovarianceMatrix() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the estimated asymptotic covariance matrix of the coefficients.
getCovariancesSwept() - Method in class com.imsl.stat.StepwiseRegression
Returns the results after cov has been swept for the columns corresponding to the variables in the model.
getCovB() - Method in class com.imsl.stat.KalmanFilter
Returns the mean squared error matrix for b divided by sigma squared.
getCovV() - Method in class com.imsl.stat.KalmanFilter
Returns the variance-covariance matrix of v divided by sigma squared.
getCPlus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the C^{+} values.
getCramersV() - Method in class com.imsl.stat.ContingencyTable
Returns Cramer's V.
getCreateImageMap() - Method in class com.imsl.chart.JspBean
Returns true if a client-side imagemap is to be created.
getCriterionOption() - Method in class com.imsl.stat.SelectionRegression
Returns the criterion option used to calculate the regression estimates.
getCriterionValues(int) - Method in class com.imsl.stat.SelectionRegression.Statistics
Returns an array containing the values of the best criterion for the number of variables considered.
getCross() - Method in class com.imsl.chart.AxisXY
Returns the value of the "Cross" attribute.
getCrossCorrelation() - Method in class com.imsl.stat.CrossCorrelation
Returns the cross-correlations between the time series x and y.
getCrossCorrelation() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the cross-correlations between the channels of x and y.
getCrossCovariance() - Method in class com.imsl.stat.CrossCorrelation
Returns the cross-covariances between the time series x and y.
getCrossCovariance() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the cross-covariances between the channels of x and y.
getCrossValidatedError() - Method in class com.imsl.datamining.CrossValidation
Returns the cross-validated error.
getCumulativeAxis() - Method in class com.imsl.chart.qc.ParetoChart
Returns the "CumulativeAxis" attribute.
getCumulativeLine() - Method in class com.imsl.chart.qc.ParetoChart
Returns the "CumulativeLine" attribute.
getCursorName() - Method in class com.imsl.io.AbstractFlatFile
Gets the name of the SQL cursor used by this ResultSet object.
getCustomMarkerFactory() - Method in class com.imsl.chart3d.Data
Returns a custom marker factory.
getCustomTransform() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "CustomTransform" attribute.
getCutpoints() - Method in class com.imsl.stat.ChiSquaredTest
Returns the cutpoints.
getDataMarkers() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the "DataMarkers" attribute containing the data markers.
getDataMarkersAxis() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the "DataMarkersAxis" attribute containing the axis associated with the data markers.
getDataType() - Method in class com.imsl.chart.ChartNode
Returns the value of the "DataType" attribute.
getDataType() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "DataType" attribute.
getDate(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDateIncrement() - Method in class com.imsl.stat.TimeSeries
Returns the date increment for this TimeSeries object.
getDates() - Method in class com.imsl.stat.TimeSeries
Returns the date array associated with the time series.
getDaysInYear(GregorianCalendar) - Method in interface com.imsl.finance.BasisPart
Returns the number of days in the year.
getDecisionTree() - Method in class com.imsl.datamining.decisionTree.DecisionTree
Returns a Tree object.
getDegreesOfFreedom() - Method in class com.imsl.stat.ChiSquaredTest
Returns the degrees of freedom in chi-squared.
getDegreesOfFreedom() - Method in class com.imsl.stat.ContingencyTable
Returns the degrees of freedom for the chi-squared tests associated with the table.
getDegreesOfFreedom() - Method in class com.imsl.stat.NormalityTest
Returns the degrees of freedom for the chi-squared goodness-of-fit test.
getDegreesOfFreedomForError() - Method in class com.imsl.stat.ANOVA
Returns the degrees of freedom for error.
getDegreesOfFreedomForModel() - Method in class com.imsl.stat.ANOVA
Returns the degrees of freedom for model.
getDensity() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Density" attribute.
getDesignVariableMeans() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the means of the design variables.
getDeviations() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the deviations used for calculating the forecast confidence limits.
getDeviations() - Method in class com.imsl.stat.ARMA
Returns the deviations used for calculating the forecast confidence limits.
getDeviations() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the deviations from each forecast used for calculating the forecast confidence limits.
getDeviations() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the deviations used for calculating the forecast confidence limits.
getDeviations() - Method in class com.imsl.stat.AutoARIMA
Returns the deviations used for calculating the forecast confidence limits.
getDeviceMarkerSize() - Method in class com.imsl.chart.Draw
Returns the marker size in device corrdinates.
getDFError() - Method in class com.imsl.stat.NonlinearRegression
Returns the degrees of freedom for error.
getDFFITS() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns DFFITS for an observation.
getDiagonalPivotThreshold() - Method in class com.imsl.math.ComplexSuperLU
Returns the threshold used for a diagonal entry to be an acceptable pivot.
getDiagonalPivotThreshold() - Method in class com.imsl.math.SuperLU
Returns the threshold used for a diagonal entry to be an acceptable pivot.
getDiffMean() - Method in class com.imsl.stat.NormTwoSample
Returns the difference in means, mean of x - mean of y.
getDimension() - Method in class com.imsl.datamining.KohonenSOM
Returns the number of weights for each node.
getDimension() - Method in class com.imsl.stat.FaureSequence
Returns the dimension of the sequence.
getDimension() - Method in interface com.imsl.stat.RandomSequence
Returns the dimension of the sequence.
getDInitial() - Method in class com.imsl.stat.ARSeasonalFit
Returns the candidate values for d to evaluate.
getDirection() - Method in class com.imsl.chart3d.DirectionalLight
Returns the value of the "Direction" attribute.
getDistanceMatrix() - Method in class com.imsl.stat.Dissimilarities
Returns the distance matrix.
getDistanceMethod() - Method in class com.imsl.stat.Dissimilarities
Returns the method used in computing the dissimilarities or similarities.
getDouble(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a double in the Java programming language.
getDouble(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a double in the Java programming language.
getDoubleAttribute(String, double) - Method in class com.imsl.chart.AbstractChartNode
Convenience routine to get a Double-valued attribute.
getDoubleBuffering() - Method in class com.imsl.chart.ChartNode
Returns the value of the "DoubleBuffering" attribute.
getDown() - Method in class com.imsl.chart.Candlestick
Returns the CandlestickItem for down days.
getDual() - Method in class com.imsl.math.QuadraticProgramming
Returns the dual (Lagrange multipliers).
getDualInfeasibility() - Method in class com.imsl.math.SparseLP
Returns the dual infeasibility of the solution.
getDualInfeasibilityTolerance() - Method in class com.imsl.math.SparseLP
Returns the dual infeasibility tolerance.
getDualSolution() - Method in class com.imsl.math.BoundedVariableLeastSquares
Returns the dual solution vector, w.
getDualSolution() - Method in class com.imsl.math.DenseLP
Returns the dual solution.
getDualSolution() - Method in class com.imsl.math.NonNegativeLeastSquares
Returns the dual solution vector, w.
getDualSolution() - Method in class com.imsl.math.SparseLP
Returns the dual solution.
getDummyMethod() - Method in class com.imsl.stat.RegressorsForGLM
Returns the dummy method.
getEffects() - Method in class com.imsl.stat.RegressorsForGLM
Returns the effects.
getEffectsColumns() - Method in class com.imsl.stat.RegressorsForGLM
Returns a mapping of effects to regressor columns.
getEnumValue(String) - Static method in class com.imsl.chart.xml.ChartXML
Returns the int corresponding to an enumeration.
getEpochSize() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the number of sample training patterns in each stage 1 epoch.
getEquilibrate() - Method in class com.imsl.math.ComplexSuperLU
Returns the equilibration flag.
getEquilibrate() - Method in class com.imsl.math.SuperLU
Returns the equilibration flag.
getEquilibrationMethod() - Method in class com.imsl.math.ComplexSuperLU
Returns information on the type of equilibration used before matrix factorization.
getEquilibrationMethod() - Method in class com.imsl.math.SuperLU
Returns information on the type of equilibration used before matrix factorization.
getError() - Method in class com.imsl.datamining.neural.BinaryClassification
Returns the error function for use by QuasiNewtonTrainer for training a binary classification network.
getError() - Method in class com.imsl.datamining.neural.MultiClassification
Returns the error function for use by QuasiNewtonTrainer for training a classification network.
getError() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the function used to compute the error to be minimized.
getErrorEstimate() - Method in class com.imsl.math.EpsilonAlgorithm
Returns the current error estimate.
getErrorEstimate() - Method in class com.imsl.math.HyperRectangleQuadrature
Returns an estimate of the relative error in the computed result.
getErrorEstimate() - Method in class com.imsl.math.Quadrature
Returns an estimate of the relative error in the computed result.
getErrorGradient() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in interface com.imsl.datamining.neural.Trainer
Returns the value of the gradient of the error function with respect to the weights.
getErrorMeanSquare() - Method in class com.imsl.stat.ANOVA
Returns the error mean square.
getErrorNumber() - Method in exception com.imsl.LicenseManagerException
Returns the error number for this exception.
getErrorStatus() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the training error status.
getErrorStatus() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Returns the error status from the trainer.
getErrorStatus() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the error status from the trainer.
getErrorStatus() - Method in interface com.imsl.datamining.neural.Trainer
Returns the error status.
getErrorStatus() - Method in class com.imsl.math.MinUnconMultiVar
Returns the non-fatal error status.
getErrorStatus() - Method in class com.imsl.math.NonlinLeastSquares
Get information about the performance of NonlinLeastSquares.
getErrorStatus() - Method in class com.imsl.math.Quadrature
Returns the non-fatal error status.
getErrorStatus() - Method in class com.imsl.stat.NonlinearRegression
Gets information about the performance of NonlinearRegression.
getErrorSumOfSquares() - Method in class com.imsl.math.Spline2DLeastSquares
Returns the weighted error sum of squares.
getErrorValue() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the value of the error function.
getErrorValue() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Returns the final value of the error function.
getErrorValue() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the final value of the error function.
getErrorValue() - Method in interface com.imsl.datamining.neural.Trainer
Returns the value of the error function minimized by the trainer.
getEstimates() - Method in class com.imsl.stat.distributions.MaximumLikelihoodEstimation
Returns the parameter estimates.
getEstimates() - Method in class com.imsl.stat.VectorAutoregression
Returns the parameter estimates (coefficients) of the vector autoregression model.
getEstimationMethod() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the estimation method used for estimating the autoregressive coefficients.
getEstimationMethod() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the method used for estimating the final autoregressive coefficients for missing value estimation methods AR_1 and AR_P.
getExactMean() - Method in class com.imsl.stat.ContingencyTable
Returns exact mean.
getExactStdev() - Method in class com.imsl.stat.ContingencyTable
Returns exact standard deviation.
getExclude() - Method in class com.imsl.stat.ARSeasonalFit
Returns the current setting for excluding or replacing the inital values in the transformed series.
getExpectedCounts() - Method in class com.imsl.stat.ChiSquaredTest
Returns the expected counts.
getExpectedMean() - Method in class com.imsl.chart.qc.CuSum
Returns the expected mean of all of the data from all of the samples.
getExpectedMean() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the expected (target) mean value.
getExpectedValues() - Method in class com.imsl.stat.ContingencyTable
Returns the expected values of each cell in the table.
getExplode() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Explode" attribute.
getExtendedLikelihoodObservations() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns a vector indicating which observations are included in the extended likelihood.
getF() - Method in class com.imsl.stat.ANOVA
Returns the F statistic.
getFactorLoadings() - Method in class com.imsl.stat.FactorAnalysis
Returns the unrotated factor loadings.
getFarMarkers() - Method in class com.imsl.chart.BoxPlot
Returns the FarMarkers node.
getFarMarkers() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the array of far markers.
getFeature() - Method in exception com.imsl.LicenseManagerException
Returns the name of the feature that could not be licensed.
getFetchDirection() - Method in class com.imsl.io.AbstractFlatFile
Returns the fetch direction for this ResultSet object.
getFetchSize() - Method in class com.imsl.io.AbstractFlatFile
Returns the fetch size for this ResultSet object.
getFillColor() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "FillColor" attribute.
getFillOutlineColor() - Method in class com.imsl.chart.ChartNode
Returns the value of the "FillOutlineColor" attribute.
getFillOutlineType() - Method in class com.imsl.chart.ChartNode
Returns the value of the "FillOutlineType" attribute.
getFillPaint() - Method in class com.imsl.chart.ChartNode
Returns the value of the "FillPaint" attribute.
getFillType() - Method in class com.imsl.chart.ChartNode
Returns the value of the "FillType" attribute.
getFinalActiveConstraints() - Method in class com.imsl.math.MinConGenLin
Returns the indices of the final active constraints.
getFinalActiveConstraintsNum() - Method in class com.imsl.math.MinConGenLin
Returns the final number of active constraints.
getFirstTick() - Method in class com.imsl.chart.Axis1D
Convenience routine to get the "FirstTick" attribute.
getFirstTick() - Method in class com.imsl.chart3d.Axis3D
Convenience routine to get the "FirstTick" attribute.
getFittedMeanSquaredError() - Method in class com.imsl.datamining.decisionTree.DecisionTree
Returns the mean squared error on the training data.
getFittedValues() - Method in class com.imsl.datamining.GradientBoosting
Returns the fitted values {f(x_i)} for a continuous response variable after gradient boosting.
getFloat(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a float in the Java programming language.
getFloat(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a float in the Java programming language.
getFloor() - Method in class com.imsl.math.ODE
Returns the value used in the norm computation.
getFont() - Method in class com.imsl.chart.AbstractChartNode
Convenience routine which gets a Font object based on the "FontName", "FontStyle" and "FontSize" attributes.
getFontName() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "FontName" attribute.
getFontSize() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "FontSize" attribute.
getFontStyle() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "FontStyle" attribute.
getForecast(int) - Method in class com.imsl.stat.ARAutoUnivariate
Returns forecasts
getForecast(int) - Method in class com.imsl.stat.ARMA
Returns forecasts
getForecast(int) - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns forecasts
getForecast() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns forecasts for the original outlier contaminated series.
getForecast() - Method in class com.imsl.stat.AutoARIMA
Returns forecasts for the original outlier contaminated series.
getForecastGradient(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the derivatives of the outputs with respect to the weights.
getForecastGradient(double[]) - Method in class com.imsl.datamining.neural.Network
Returns the derivatives of the outputs with respect to the weights.
getForecasts() - Method in class com.imsl.stat.HoltWintersExponentialSmoothing
Returns the forecasts past the series data.
getForecasts() - Method in class com.imsl.stat.VectorAutoregression
Returns the h-step ahead forecast at times t=nT, nT+1, ..., T, where h=1,2, ..., maxStepsAhead.
getFormatter() - Static method in class com.imsl.datamining.neural.EpochTrainer
Returns the logging Formatter object.
getFormatter() - Static method in class com.imsl.datamining.neural.LeastSquaresTrainer
Returns the logging Formatter object.
getFormatter() - Static method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the logging formatter object.
getForwardErrorBound() - Method in class com.imsl.math.ComplexSuperLU
Returns the estimated forward error bound for each solution vector.
getForwardErrorBound() - Method in class com.imsl.math.SuperLU
Returns the estimated forward error bound for the solution vector.
getFrequencyColumn() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the column index of x containing the frequency of response for each observation.
getFrequencyColumn() - Method in class com.imsl.stat.ProportionalHazards
Returns the column index of x containing the frequency of response for each observation.
getFrequencyTable() - Method in class com.imsl.stat.TableOneWay
Returns the one-way frequency table.
getFrequencyTable(double, double) - Method in class com.imsl.stat.TableOneWay
Returns a one-way frequency table using known bounds.
getFrequencyTable() - Method in class com.imsl.stat.TableTwoWay
Returns the two-way frequency table.
getFrequencyTable(double, double, double, double) - Method in class com.imsl.stat.TableTwoWay
Compute a two-way frequency table using intervals of equal length and user supplied upper and lower bounds, xLowerBound, xUpperBound, yLowerBound, yUpperBound.
getFrequencyTableUsingClassmarks(double[]) - Method in class com.imsl.stat.TableOneWay
Returns the one-way frequency table using class marks.
getFrequencyTableUsingClassmarks(double[], double[]) - Method in class com.imsl.stat.TableTwoWay
Returns the two-way frequency table using class marks.
getFrequencyTableUsingCutpoints(double[]) - Method in class com.imsl.stat.TableOneWay
Returns the one-way frequency table using cutpoints.
getFrequencyTableUsingCutpoints(double[], double[]) - Method in class com.imsl.stat.TableTwoWay
Returns the two-way frequency table using cutpoints.
getFrequentItemsets(int[][], int, int, double) - Static method in class com.imsl.datamining.Apriori
Computes the frequent itemsets in the transaction set x.
getFrom() - Method in class com.imsl.datamining.neural.Link
Returns the origination Node for this Link.
getFTest() - Method in class com.imsl.stat.NormTwoSample
Returns the F test value of the F test for equality of variances.
getFTestDFdenominator() - Method in class com.imsl.stat.NormTwoSample
Returns the denominator degrees of freedom of the F test for equality of variances.
getFTestDFnumerator() - Method in class com.imsl.stat.NormTwoSample
Returns the numerator degrees of freedom of the F test for equality of variances.
getFTestP() - Method in class com.imsl.stat.NormTwoSample
Returns the probability of a larger F in absolute value for the F test for equality of variances, assuming equal variances.
getGARCH() - Method in class com.imsl.stat.GARCH
Returns the estimated values of the GARCH coefficients.
getGaussLegendreDegree() - Method in class com.imsl.math.FeynmanKac
Returns the number of quadrature points used in the Gauss-Legendre quadrature formula.
getGradient() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Gradient" attribute.
getGradient() - Method in class com.imsl.stat.ProportionalHazards
Returns the inverse of the Hessian times the gradient vector, computed at the initial estimates.
getGradients() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the gradients for the final parameter estimates.
getGradientTolerance() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the gradient tolerance for the convergence algorithm.
getGrid() - Method in class com.imsl.chart.Axis1D
Returns the grid node associated with this axis.
getGridPolar() - Method in class com.imsl.chart.Polar
Returns the grid.
getGridType() - Method in class com.imsl.datamining.KohonenSOM
Returns the grid type.
getGroupCounts() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the group counts.
getGroupInformation() - Method in class com.imsl.stat.ANOVA
Returns information concerning the groups.
getGroups() - Method in class com.imsl.stat.TableMultiWay
Returns the number of observations (rows) in each group.
getGroupTotal(double) - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the total number in the group for the specified group value.
getGSquared() - Method in class com.imsl.stat.ContingencyTable
Returns the likelihood ratio G2 (chi-squared).
getGSquaredP() - Method in class com.imsl.stat.ContingencyTable
Returns the probability of a larger G2 (chi-squared).
getGuess() - Method in class com.imsl.math.GenMinRes
Returns the initial guess of the solution.
getHeatmapLabels() - Method in class com.imsl.chart.Heatmap
Returns the value of the "HeatmapLabels" attribute.
getHeatmapLegend() - Method in class com.imsl.chart.Heatmap
Returns the heatmap legend.
getHessian() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the Hessian computed at the initial parameter estimates.
getHessian() - Method in class com.imsl.stat.distributions.MaximumLikelihoodEstimation
Returns the Hessian of the log-likelihood function evaluated at the current parameter estimates.
getHessian() - Method in class com.imsl.stat.ProportionalHazards
Returns the inverse of the Hessian of the negative of the log-likelihood, computed at the initial estimates.
getHessianOption() - Method in class com.imsl.stat.ProportionalHazards
Returns the boolean used to indicate whether or not to compute the Hessian and gradient at the initial estimates.
getHiddenLayers() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the HiddenLayers in this network.
getHigh() - Method in class com.imsl.chart.ErrorBar
Convenience routine to get the "High" attribute.
getHigh() - Method in class com.imsl.chart.HighLowClose
Convenience routine to get the "High" attribute.
getHistory() - Method in class com.imsl.stat.StepwiseRegression
Returns the stepwise regression history for the independent variables.
getHoldability() - Method in class com.imsl.io.FlatFile
Retrieves the holdability of this ResultSet object.
getHREF() - Method in class com.imsl.chart.ChartNode
Returns the value of the "HREF" attribute.
getHREF() - Method in class com.imsl.chart.DrawMap
Returns the current HREF string.
getId() - Method in class com.imsl.chart.JspBean
Returns the identifier number for the chart.
getImage() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Image" attribute.
getImageMap() - Method in class com.imsl.chart.JspBean
Returns an HTML for the client-side imagemap.
getImageTag() - Method in class com.imsl.chart.JspBean
Returns an HTML image tag.
getIncidenceMatrix() - Method in class com.imsl.stat.Covariances
Returns the incidence matrix.
getIndependentVariables(int) - Method in class com.imsl.stat.SelectionRegression.Statistics
Returns the identification numbers for the independent variables for the number of variables considered and in the same order as the criteria returned by SelectionRegression.Statistics.getCriterionValues(int).
getIndex() - Method in class com.imsl.datamining.neural.Layer
Returns the index of this Layer.
getIndex() - Method in class com.imsl.stat.Dissimilarities
Returns the indices of the rows (columns) used in computing the distance measure.
getInfo() - Method in class com.imsl.math.SVD
Returns convergence information about S, U, and V.
getInitialCMinus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the initial value of C^{-}.
getInitialCPlus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the initial value of C^{+}.
getInitialEstimates() - Method in class com.imsl.stat.ProportionalHazards
Gets the initial parameter estimates.
getInitialStepsize() - Method in class com.imsl.math.FeynmanKac
Returns the starting step size for the integration.
getInitialStepsize() - Method in class com.imsl.math.ODE
Returns the initial internal step size.
getInnovationVariance() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final estimate for the innovation variance.
getInnovationVariance() - Method in class com.imsl.stat.ARMA
Returns the variance of the random shock.
getInnovationVariance() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the estimated innovation variance of this series.
getInputLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the InputLayer.
getInputLayer() - Method in class com.imsl.datamining.neural.Network
Returns the InputLayer object.
getInt(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as an int in the Java programming language.
getInt(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as an int in the Java programming language.
getIntegerAttribute(String, int) - Method in class com.imsl.chart.AbstractChartNode
Convenience routine to get an Integer-valued attribute.
getIntegrationMethod() - Method in class com.imsl.math.OdeAdamsGear
Returns the integration method used.
getIntercept() - Method in class com.imsl.stat.StepwiseRegression
Returns the intercept.
getItemset(int) - Method in class com.imsl.datamining.Itemsets
Returns a particular itemset.
getItemsetsMatrix() - Method in class com.imsl.datamining.Itemsets
Returns the set of Itemsets as an integer matrix.
getIterationCount() - Method in class com.imsl.math.DenseLP
Returns the iteration count.
getIterationCount() - Method in class com.imsl.math.SparseLP
Returns the number of iterations used by the primal-dual solver.
getIterations() - Method in class com.imsl.datamining.KohonenSOMTrainer
Returns the number of iterations used for training.
getIterations() - Method in class com.imsl.math.BoundedVariableLeastSquares
Returns the number of iterations used to find the solution.
getIterations() - Method in class com.imsl.math.ConjugateGradient
Returns the number of iterations needed by the conjugate gradient algorithm.
getIterations() - Method in class com.imsl.math.GenMinRes
Returns the actual number of GMRES iterations used.
getIterations() - Method in class com.imsl.math.MinConNLP
Returns the actual number of iterations used.
getIterations() - Method in class com.imsl.math.MinUnconMultiVar
Returns the number of iterations used to compute a minimum.
getIterations() - Method in class com.imsl.math.NonNegativeLeastSquares
Returns the number of iterations used to find the solution.
getIterationsArray() - Method in class com.imsl.datamining.GradientBoosting
Returns the array of different values for the number of iterations.
getIterativeRefinement() - Method in class com.imsl.math.ComplexSuperLU
Returns a value specifying whether iterative refinement is to be performed or not.
getIterativeRefinement() - Method in class com.imsl.math.SuperLU
Returns a value specifying whether iterative refinement is to be performed or not.
getJackknifeResidual() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Jackknife Residual for an observation.
getJacobi() - Method in class com.imsl.math.ConjugateGradient
Returns the Jacobi preconditioning matrix.
getJacobian() - Method in class com.imsl.math.BoundedLeastSquares
Returns the Jacobian at the approximate solution.
getKeyboard() - Method in class com.imsl.chart3d.Chart3D
Returns the value of the "Keyboard" attribute.
getKnots() - Method in class com.imsl.math.BSpline
Returns a copy of the knot sequence.
getKurtosis() - Method in class com.imsl.stat.Summary
Returns the kurtosis.
getL() - Method in class com.imsl.math.ComplexLU
Returns the lower triangular portion of the LU factorization of A.
getL() - Method in class com.imsl.math.LU
Returns the lower triangular portion of the LU factorization of A.
getLabels() - Method in class com.imsl.chart.AxisLabel
Returns the "Labels" attribute.
getLabels() - Method in class com.imsl.chart.AxisRLabel
Returns the "Labels" attribute.
getLabels() - Method in class com.imsl.chart.Treemap
Returns the value of the "TreemapLabels" attribute.
getLabels() - Method in class com.imsl.chart3d.AxisLabel
Returns the "Labels" attribute.
getLabelType() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "LabelType" attribute.
getLagrangeMultiplierEst() - Method in class com.imsl.math.MinConGenLin
Returns the Lagrange multiplier estimates of the final active constraints.
getLagrangeMultiplierEst() - Method in class com.imsl.math.MinConNLP
Returns the Lagrange multiplier estimates of the constraints.
getLambda() - Method in class com.imsl.chart.qc.EWMA
Returns the value of the attribute "Lambda".
getLargestCPRatio() - Method in class com.imsl.math.SparseLP
Returns the ratio of the largest complementarity product to the average.
getLargestDiagonalElement() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the largest diagonal element of the Cholesky factor.
getLargestDiagonalElement() - Method in class com.imsl.math.SparseCholesky
Returns the largest diagonal element of the Cholesky factor.
getLastParameterUpdates() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the last parameter updates (excluding step halvings).
getLastUpdates() - Method in class com.imsl.stat.ProportionalHazards
Gets the last parameter updates.
getLayer() - Method in class com.imsl.datamining.neural.Node
Returns the Layer in which this Node exists.
getLearningCoefficient(int) - Method in class com.imsl.datamining.KohonenSOMTrainer
Returns the learning coefficient.
getLeftEndTangent() - Method in class com.imsl.math.CsTCB
Returns the value of the tangent at the leftmost endpoint.
getLeftSons() - Method in class com.imsl.chart.Dendrogram
Convenience routine to get the "LeftSons" attribute.
getLegend() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Legend" attribute.
getLength() - Method in class com.imsl.stat.TimeSeries
Returns the length of the time series.
getLevels() - Method in class com.imsl.chart.Dendrogram
Convenience routine to get the "Levels" attribute.
getLeverage() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Leverage for an observation.
getLicensePath() - Method in exception com.imsl.LicenseManagerException
Returns the license file path for this exception.
getLifeTable() - Method in class com.imsl.stat.LifeTables
Compute a cohort table.
getLift() - Method in class com.imsl.datamining.AssociationRule
The lift measure of the association rule.
getLightColor() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "LightColor" attribute.
getLightingEnabled() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "LightingEnabled" attribute.
getLikelihood() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final estimate for L=e^{-(mbox{AIC} - 2p)/2}, where p is the AR order, AIC is Akaike's Information Criterion, and L is the likelihood function evaluated for the optimum autoregressive model.
getLikelihood() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the final estimate for -2ln(L), where L is equal to the likelihood function evaluated using the final parameter estimates.
getLineColor() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "LineColor" attribute.
getLineDashPattern() - Method in class com.imsl.chart.ChartNode
Returns the value of the "LineDashPattern" attribute.
getLineWidth() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "LineWidth" attribute.
getLinks() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Return all of the Links in this Network.
getLinks() - Method in class com.imsl.datamining.neural.Network
Returns an array containing the Link objects in the Network.
getListCells() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable
Returns for each row, a list of the levels of nKeys corresponding classification variables that describe a cell.
getLocale() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Locale" attribute.
getLocalizedMessage() - Method in exception com.imsl.LicenseManagerException
Returns the localized error message for this exception.
getLogDeterminant() - Method in class com.imsl.stat.KalmanFilter
Returns the natural log of the product of the nonzero eigenvalues of P where P * sigma2 is the variance-covariance matrix of the observations.
getLogger() - Static method in class com.imsl.datamining.neural.EpochTrainer
Returns the Logger object.
getLogger() - Static method in class com.imsl.datamining.neural.LeastSquaresTrainer
Returns the Logger object.
getLogger() - Static method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the Logger object.
getLogger() - Method in class com.imsl.math.GenMinRes
Returns the logger object.
getLogger() - Method in class com.imsl.math.MinConNLP
Returns the logger object.
getLogger() - Method in class com.imsl.math.ZeroSystem
Returns the logger object.
getLogger() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the logger object.
getLogger() - Method in class com.imsl.stat.ProportionalHazards
Returns the logger object and enables logging.
getLogLikelihood(double[], double[]) - Method in class com.imsl.stat.distributions.MaximumLikelihoodEstimation
Returns the log-likelihood.
getLogLikelihood() - Method in class com.imsl.stat.GARCH
Returns the value of Log-likelihood function evaluated at the estimated parameter array.
getLogLikelihood(double) - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the Kaplan-Meier log-likelihood of the group with the specified group value.
getLong(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a long in the Java programming language.
getLong(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a long in the Java programming language.
getLossType() - Method in class com.imsl.datamining.GradientBoosting
Returns the current loss function type.
getLossValue() - Method in class com.imsl.datamining.GradientBoosting
Returns the loss function value.
getLow() - Method in class com.imsl.chart.ErrorBar
Convenience routine to get the "Low" attribute.
getLow() - Method in class com.imsl.chart.HighLowClose
Convenience routine to get the "Low" attribute.
getLowerAdjacentValue() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the lower adjacent value.
getLowerBound(int) - Method in class com.imsl.io.MPSReader
Returns the lower bound for a variable.
getLowerBound() - Method in class com.imsl.math.SparseLP
Returns the lower bound on the variables.
getLowerCICommonVariance() - Method in class com.imsl.stat.NormTwoSample
Returns the lower confidence limits for the common, or pooled, variance.
getLowerCIDiff() - Method in class com.imsl.stat.NormTwoSample
Returns the lower confidence limit for the mean of the first population minus the mean of the second for equal or unequal variances depending on the value set by setUnequalVariances.
getLowerCIMean() - Method in class com.imsl.stat.NormOneSample
Returns the lower confidence limit for the mean.
getLowerCIRatioVariance() - Method in class com.imsl.stat.NormTwoSample
Returns the approximate lower confidence limit for the ratio of the variance of the first population to the second.
getLowerCIVariance() - Method in class com.imsl.stat.NormOneSample
Returns the lower confidence limits for the variance.
getLowerControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the lower control limit.
getLowerQuartile() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the lower quartile value.
getLowerRange(int) - Method in class com.imsl.io.MPSReader
Returns the lower range value for a constraint equation.
getMA() - Method in class com.imsl.stat.ARMA
Returns the final moving average parameter estimates.
getMA() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the final moving average parameter estimates.
getMA() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the final moving average parameter estimates.
getMA() - Method in class com.imsl.stat.AutoARIMA
Returns the final moving average parameter estimates of the optimum model.
getMahalanobis() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the Mahalanobis distances between the group means.
getMajorTick() - Method in class com.imsl.chart.Axis1D
Returns the major tick node associated with this axis.
getMajorTick() - Method in class com.imsl.chart3d.Axis3D
Returns the major tick node associated with this axis.
getMannWhitney() - Method in class com.imsl.stat.WilcoxonRankSum
Returns the Mann-Whitney test statistic.
getMap() - Method in class com.imsl.chart.DrawMap
Returns the body of the HTML imagemap.
getMapName() - Method in class com.imsl.chart.JspBean
Returns the name of the client-size imagemap.
getMarkerColor() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "MarkerColor" attribute.
getMarkerDashPattern() - Method in class com.imsl.chart.ChartNode
Returns the value of the "MarkerPattern" attribute.
getMarkerPulsingCycle() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerPulsingCycle" attribute.
getMarkerPulsingCycleOffset() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerPulsingCycleOffset" attribute.
getMarkerPulsingMaximumScale() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerPulsingMaximumScale" attribute.
getMarkerPulsingMinimumScale() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerPulsingMinimumScale" attribute.
getMarkerRotatingAxis() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerRotatingAxis" attribute.
getMarkerRotatingCycle() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerRotatingCycle" attribute.
getMarkerRotatingCycleOffset() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerRotatingCycleOffset" attribute.
getMarkerSize() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "MarkerSize" attribute.
getMarkerThickness() - Method in class com.imsl.chart.ChartNode
Returns the value of the "MarkerThickness" attribute.
getMarkerType() - Method in class com.imsl.chart.ChartNode
Returns the value of the "MarkerType" attribute.
getMarkerType() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerType" attribute.
getMaterial() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Material" attribute.
getMaxClass() - Method in class com.imsl.stat.ProportionalHazards
Returns the upper bound used on the sum of the number of distinct values found among the classification variables in x.
getMaxDepth() - Method in class com.imsl.datamining.decisionTree.DecisionTree
Returns the maximum depth a tree is allowed to have.
getMaxDifference() - Method in class com.imsl.stat.NormalityTest
Returns the maximum absolute difference between the empirical and the theoretical distributions for the Lilliefors test.
getMaxEvaluations() - Method in class com.imsl.math.ZerosFunction
Returns the maximum number of function evaluations allowed.
getMaximum() - Method in class com.imsl.stat.Summary
Returns the maximum.
getMaximum() - Method in class com.imsl.stat.TableOneWay
Returns maximum value of x.
getMaximumBDFOrder() - Method in class com.imsl.math.FeynmanKac
Returns the maximum order of the BDF formulas.
getMaximumDifference() - Method in class com.imsl.stat.KolmogorovOneSample
Returns D^{+}, the maximum difference between the theoretical and empirical CDF's.
getMaximumDifference() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns D^{+}, the maximum difference between the theoretical and empirical CDF's.
getMaximumFunctionEvaluations() - Method in class com.imsl.math.OdeAdamsGear
Returns the maximum number of function evaluations of y' allowed.
getMaximumLikelihood() - Method in class com.imsl.stat.ProportionalHazards
Returns the maximized log-likelihood.
getMaximumStepsize() - Method in class com.imsl.math.FeynmanKac
Returns the maximum internal step size used by the integrator.
getMaximumStepsize() - Method in class com.imsl.math.ODE
Returns the maximum internal step size.
getMaximumTime() - Method in class com.imsl.math.MinConNLP
Returns the maximum time allowed for the solve step.
getMaximumValue() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the maximum value of the observations.
getMaximumValue() - Method in class com.imsl.chart.qc.ControlLimit
Returns the maximum value of this control limit line.
getMaximumX() - Method in class com.imsl.stat.TableTwoWay
Returns the maximum value of x.
getMaximumY() - Method in class com.imsl.stat.TableTwoWay
Returns the maximum value of y.
getMaxIterations() - Method in class com.imsl.math.ConjugateGradient
Returns the maximum number of iterations allowed.
getMaxIterations() - Method in class com.imsl.math.Eigen
Returns the maximum number of iterations.
getMaxIterations() - Method in class com.imsl.math.GenMinRes
Returns the maximum number of iterations allowed.
getMaxIterations() - Method in class com.imsl.math.SparseLP
Returns the maximum number of iterations allowed for the primal-dual solver.
getMaxIterations() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the value currently being used as the maximum number of iterations allowed in the nonlinear equation solver used in both the method of moments and least-squares algorithms.
getMaxIterations() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the maximum number of estimation iterations used by missing value estimation methods AR_1 and AR_P.
getMaxIterations() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the maximum number of iterations.
getMaxIterations() - Method in class com.imsl.stat.ProportionalHazards
Return the maximum number of iterations allowed.
getMaxKrylovDim() - Method in class com.imsl.math.GenMinRes
Returns the maximum Krylov subspace dimension, i.e., the maximum allowable number of GMRES iterations allowed before restarting.
getMaxlag() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the current value used to represent the maximum number of autoregressive lags to achieve the minimum AIC.
getMaxlag() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the current value of autoregressive lags used in the AR_P estimation method.
getMaxlag() - Method in class com.imsl.stat.ARSeasonalFit
Returns the maximum lag used to fit the AR(p) model.
getMaxNodes() - Method in class com.imsl.datamining.decisionTree.DecisionTree
Returns the maximum number of TreeNode instances allowed in a tree.
getMaxNumberOfCategories() - Method in class com.imsl.datamining.PredictiveModel
Returns the maximum number of categorical variables allowed.
getMaxOrder() - Method in class com.imsl.math.OdeAdamsGear
Returns the highest order formula to use of implicit METHOD_ADAMS type or METHOD_BDF type.
getMaxSteps() - Method in class com.imsl.math.FeynmanKac
Returns the maximum number of internal steps allowed.
getMaxSteps() - Method in class com.imsl.math.ODE
Returns the maximum number of internal steps allowed.
getMean() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the mean used to center the time series z.
getMean() - Method in class com.imsl.stat.ARMA
Returns an update of the mean of the time series z.
getMean() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the mean value used to center the series.
getMean() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the mean used to center the time series.
getMean() - Method in class com.imsl.stat.AutoCorrelation
Returns the mean of the time series x.
getMean() - Method in class com.imsl.stat.LogNormalDistribution
Returns the lognormal probability distribution mean parameter.
getMean() - Method in class com.imsl.stat.NormalDistribution
Returns the population mean of xData.
getMean() - Method in class com.imsl.stat.NormOneSample
Returns the mean of the sample.
getMean() - Method in class com.imsl.stat.Summary
Returns the population mean.
getMeanOfY() - Method in class com.imsl.stat.ANOVA
Returns the mean of the response (dependent variable).
getMeans(double[][], int[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns a table of means for each continuous attribute in continuousData segmented by the target classes in classificationData.
getMeans() - Method in class com.imsl.stat.ANCOVA
Returns a matrix containing the unadjusted means for the covariates and the response variate and the means for the response variate adjusted for the covariates.
getMeans() - Method in class com.imsl.stat.ANOVAFactorial
Returns the subgroup means.
getMeans() - Method in class com.imsl.stat.Covariances
Returns the means of the variables in x.
getMeans() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the variable means.
getMeans() - Method in class com.imsl.stat.ProportionalHazards
Returns the means of the design variables.
getMeanSampleSize() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the value of the attribute "MeanSampleSize".
getMeanSquaredPredictionError() - Method in class com.imsl.datamining.BootstrapAggregation
Returns the mean squared prediction error.
getMeanSquaredPredictionError() - Method in class com.imsl.datamining.decisionTree.DecisionTree
Returns the mean squared error.
getMeanX() - Method in class com.imsl.stat.CrossCorrelation
Returns the mean of the time series x.
getMeanX() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the mean of each channel of x.
getMeanX() - Method in class com.imsl.stat.NormTwoSample
Returns the mean of the first sample, x.
getMeanY() - Method in class com.imsl.stat.CrossCorrelation
Returns the mean of the time series y.
getMeanY() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the mean of each channel of y.
getMeanY() - Method in class com.imsl.stat.NormTwoSample
Returns the mean of the second sample, y.
getMedian() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the median value.
getMedianLowerConfidenceInterval() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the lower confidence interval for the median.
getMedianUpperConfidenceInterval() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the upper confidence interval for the median.
getMergeCategoriesSigLevel() - Method in class com.imsl.datamining.decisionTree.CHAID
Returns the significance level for merging categories.
getMetaData() - Method in class com.imsl.io.AbstractFlatFile
Retrieves the number, types and properties of this ResultSet object's columns.
getMethod() - Method in class com.imsl.math.GenMinRes
Returns the implementation method to be used.
getMethod() - Method in class com.imsl.stat.ClusterHierarchical
Returns the clustering method used.
getMinimum() - Method in class com.imsl.stat.Summary
Returns the minimum.
getMinimum() - Method in class com.imsl.stat.TableOneWay
Returns the minimum value of x.
getMinimumDifference() - Method in class com.imsl.stat.KolmogorovOneSample
Returns D^{-}, the minimum difference between the theoretical and empirical CDF's.
getMinimumDifference() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns D^{-}, the minimum difference between the theoretical and empirical CDF's.
getMinimumStepsize() - Method in class com.imsl.math.ODE
Returns the minimum internal step size.
getMinimumValue() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the minimum value of the observations.
getMinimumValue() - Method in class com.imsl.chart.qc.ControlLimit
Returns the minimum value of this control limit line.
getMinimumX() - Method in class com.imsl.stat.TableTwoWay
Returns the minimum value of x.
getMinimumY() - Method in class com.imsl.stat.TableTwoWay
Returns the minimum value of y.
getMinObsPerChildNode() - Method in class com.imsl.datamining.decisionTree.DecisionTree
Returns the minimum number of observations that are required for any child node before performing a split.
getMinObsPerNode() - Method in class com.imsl.datamining.decisionTree.DecisionTree
Returns the minimum number of observations that are required in a node before performing a split.
getMinorTick() - Method in class com.imsl.chart.Axis1D
Returns the minor tick node associated with this axis.
getMinusLogLikelihood() - Method in class com.imsl.stat.distributions.MaximumLikelihoodEstimation
Returns minus the log-likelihood evaluated at the parameter estimates.
getMissingIndicator() - Method in class com.imsl.stat.TimeSeries
Returns an array of missing value indicators.
getMissingTestYFlag() - Method in class com.imsl.datamining.GradientBoosting
Returns the flag that sets whether the test data is missing the response variable data.
getMissingTimes() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns an int array of the times with missing values.
getMissingValueMethod() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the current missing value estimation method.
getMLEs(double[]) - Method in class com.imsl.stat.distributions.NormalPD
Returns the mean and standard deviation of the sample data.
getModelCoefficients() - Method in class com.imsl.stat.ANCOVA
Returns a matrix containing statistics for the regression coefficients for the model assuming parallelism.
getModelErrorStdev() - Method in class com.imsl.stat.ANOVA
Returns the estimated standard deviation of the model error.
getModelMeanSquare() - Method in class com.imsl.stat.ANOVA
Returns the model mean square.
getMonthBasis() - Method in class com.imsl.finance.DayCountBasis
Returns the (days in month) portion of the Day Count Basis.
getMRBar() - Method in class com.imsl.chart.qc.XmR
Returns the expected mean of of all of the moving ranges of two observations.
getMultinomialResponse() - Method in class com.imsl.datamining.GradientBoosting
Returns the multinomial representation of the response variable.
getName() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Name" attribute.
getName() - Method in class com.imsl.io.MPSReader
Returns the name of the MPS problem.
getName() - Method in class com.imsl.io.MPSReader.Row
Returns the name of this row.
getNameBounds() - Method in class com.imsl.io.MPSReader
Returns the name of the BOUNDS set.
getNameColumn(int) - Method in class com.imsl.io.MPSReader
Returns the name of a constraint column.
getNameObjective() - Method in class com.imsl.io.MPSReader
Returns the name of the free row containing the objective.
getNameRanges() - Method in class com.imsl.io.MPSReader
Returns the name of the RANGES set.
getNameRHS() - Method in class com.imsl.io.MPSReader
Returns the name of the RHS section.
getNameRow(int) - Method in class com.imsl.io.MPSReader
Returns the name of a contraint row.
getNCells() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable
Returns the number of non-empty cells.
getNCharacterStream(int) - Method in class com.imsl.io.FlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.
getNCharacterStream(String) - Method in class com.imsl.io.FlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.
getNClob(int) - Method in class com.imsl.io.FlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a NClob object in the Java programming language.
getNClob(String) - Method in class com.imsl.io.FlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a NClob object in the Java programming language.
getNeighborhoodType() - Method in class com.imsl.datamining.KohonenSOM
Returns the neighborhood type for the rectangular grid.
getNeighborhoodValue(int, double) - Method in class com.imsl.datamining.KohonenSOMTrainer
Returns the neighborhood function value.
getNetwork() - Method in class com.imsl.datamining.neural.BinaryClassification
Returns the network being used for classification.
getNetwork() - Method in class com.imsl.datamining.neural.MultiClassification
Returns the network being used for classification.
getNLost() - Method in class com.imsl.stat.ARSeasonalFit
Returns the number of values in the initial part of the series lost to differencing.
getNMinus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns N^{-}, the number of consecutive periods that the cusums C_i^{-} have been nonzero.
getNode() - Method in class com.imsl.chart.PickEvent
Gets this ChartNode.
getNode(int) - Method in class com.imsl.datamining.decisionTree.Tree
Returns a copy of the specified node of the decision tree.
getNodeAssigments(double[][]) - Method in class com.imsl.datamining.decisionTree.DecisionTree
Returns the terminal node assignments for each row of the test data.
getNodeId() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the id of the current node.
getNodes() - Method in class com.imsl.datamining.decisionTree.Tree
Returns nodes within a decision tree.
getNodes() - Method in class com.imsl.datamining.neural.InputLayer
Return the Perceptrons in the InputLayer.
getNodes() - Method in class com.imsl.datamining.neural.Layer
Return a list of the Perceptrons in this Layer.
getNodes() - Method in class com.imsl.datamining.neural.OutputLayer
Return the Perceptrons in the OutputLayer.
getNodeSplitValue() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the value around which the node may be split, if the split variable is of a continuous type.
getNodeValueIndicator(int) - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the indicator value for the i-th value of the split variable in the current node, if the split variable is of discrete type.
getNodeValuesIndicator() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the array indicating which values of the split variable apply in the current node, if the split variable is of discrete type.
getNodeVariableId() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the id of the variable that defines the split in the current node.
getNorm() - Method in class com.imsl.math.ODE
Returns the switch for determining the error norm.
getNormalScores(double[]) - Method in class com.imsl.stat.Ranks
Gets the expected value of normal order statistics (for tied observations, the average of the expected normal scores).
getNotch() - Method in class com.imsl.chart.BoxPlot
Gets the "Notch" attribute value.
getNPlus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns N^{+}, the number of consecutive periods that the cusums C_i^{+} have been nonzero.
getNRowsMissing() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the number of rows of data in x that contain missing values in one or more specific columns of x.
getNString(int) - Method in class com.imsl.io.FlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a String in the Java programming language.
getNString(String) - Method in class com.imsl.io.FlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a String in the Java programming language.
getNumber() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Number" attribute.
getNumberAtRisk() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the number of individuals at risk at each failure point.
getNumberFormat() - Method in class com.imsl.math.PrintMatrixFormat
Returns the NumberFormat to be used in formatting double and Complex entries.
getNumberGridPointsX() - Method in class com.imsl.chart3d.Surface
Returns the value of the "NumberGridPointsX" attribute.
getNumberGridPointsY() - Method in class com.imsl.chart3d.Surface
Returns the value of the "NumberGridPointsY" attribute.
getNumberMissing() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the number of missing values in the original series
getNumberMissing() - Method in class com.imsl.stat.KolmogorovOneSample
Returns the number of missing values in the data.
getNumberMissingX() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns the number of missing values in the x sample.
getNumberMissingX() - Method in class com.imsl.stat.WilcoxonRankSum
Returns the number of missing observations detected in x.
getNumberMissingY() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns the number of missing values in the y sample.
getNumberMissingY() - Method in class com.imsl.stat.WilcoxonRankSum
Returns the number of missing observations detected in y.
getNumberObservations() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the number of observations.
getNumberOfBackcasts() - Method in class com.imsl.stat.ARMA
Returns the number of backcasts used to calculate the AR coefficients for the time series z.
getNumberOfBinaryConstraints() - Method in class com.imsl.io.MPSReader
Returns the number of binary constraints.
getNumberOfCases() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the number of cases in the training data that fall into the current node.
getNumberOfChildren() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the number of child nodes associated with the current node.
getNumberOfClasses() - Method in class com.imsl.datamining.decisionTree.Tree
Returns the number of classes assumed by the response variable, if the response variable is categorical.
getNumberOfClasses() - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter
Retrieves the number of classes in the nominal variable.
getNumberOfClasses() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Retrieves the number of categories associated with this ordinal variable.
getNumberOfClasses() - Method in class com.imsl.datamining.PredictiveModel
Returns the number of unique classes found in the categorical response data.
getNumberOfCoefficients() - Method in class com.imsl.stat.ProportionalHazards
Returns the number of estimated coefficients in the model.
getNumberOfColumns() - Method in class com.imsl.datamining.KohonenSOM
Returns the number of columns of the node grid.
getNumberOfColumns() - Method in class com.imsl.datamining.PredictiveModel
Returns the number of columns in xy.
getNumberOfColumns() - Method in class com.imsl.io.MPSReader
Returns the number of columns in the constraint matrix.
getNumberOfColumns() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the number of columns in the matrix.
getNumberOfColumns() - Method in class com.imsl.math.SparseMatrix
Returns the number of columns in the matrix.
getNumberOfComplexityValues() - Method in class com.imsl.datamining.decisionTree.DecisionTree
Return the number of cost complexity values determined.
getNumberOfEpochs() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the number of epochs used during stage I training.
getNumberOfEvaluations() - Method in class com.imsl.math.ZerosFunction
Returns the actual number of function evaluations performed.
getNumberOfFailures() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the number of failures which occurred at each failure point.
getNumberOfFcnEvals() - Method in class com.imsl.math.OdeAdamsGear
Returns the number of function evaluations of y' made.
getNumberOfInputs() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the number of inputs to the Network.
getNumberOfInputs() - Method in class com.imsl.datamining.neural.Network
Returns the number of Network inputs.
getNumberOfIntegerConstraints() - Method in class com.imsl.io.MPSReader
Returns the number of integer constraints.
getNumberOfItemsets() - Method in class com.imsl.datamining.Itemsets
Returns the number of itemsets in this Itemsets.
getNumberOfIterations() - Method in class com.imsl.datamining.GradientBoosting
Returns the current setting for the number of iterations to use in the gradient boosting algorithm.
getNumberOfJacobianEvals() - Method in class com.imsl.math.OdeAdamsGear
Returns the number of Jacobian matrix evaluations used.
getNumberOfLevels() - Method in class com.imsl.datamining.decisionTree.Tree
Returns the number of levels or depth of a tree.
getNumberOfLinks() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the number of Links in the Network.
getNumberOfLinks() - Method in class com.imsl.datamining.neural.Network
Returns the number of Network Links among the nodes.
getNumberOfMissing() - Method in class com.imsl.datamining.PredictiveModel
Returns the number of missing values of the response variable found in the data xy.
getNumberOfMissing() - Method in class com.imsl.stat.ANCOVA
Returns the number of cases with missing values in covariates or responses.
getNumberOfMissingRows() - Method in class com.imsl.stat.RegressorsForGLM
Returns the number of rows in the regressors matrix containing NaN (not a number).
getNumberOfNodes() - Method in class com.imsl.datamining.decisionTree.Tree
Returns the number of nodes (size of a tree).
getNumberOfNonZeros() - Method in class com.imsl.io.MPSReader
Returns the number of nonzeros in the constraint matrix.
getNumberOfNonZeros() - Method in class com.imsl.io.MPSReader.Row
Returns the number of nonzero elements in this row.
getNumberOfNonzeros() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the number of nonzeros in the Cholesky factor.
getNumberOfNonZeros() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the number of nonzeros in the matrix.
getNumberOfNonzeros() - Method in class com.imsl.math.SparseCholesky
Returns the number of nonzeros in the Cholesky factor.
getNumberOfNonZeros() - Method in class com.imsl.math.SparseMatrix
Returns the number of nonzeros in the matrix.
getNumberOfObservations() - Method in class com.imsl.stat.Summary
Returns the number of non-missing observations.
getNumberOfOutliers() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the number of outliers detected.
getNumberOfOutliers() - Method in class com.imsl.stat.AutoARIMA
Returns the number of outliers detected.
getNumberOfOutputs() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the number of outputs from the Network.
getNumberOfOutputs() - Method in class com.imsl.datamining.neural.Network
Returns the number of Network output Perceptrons.
getNumberOfParameters() - Method in class com.imsl.stat.distributions.ProbabilityDistribution
Returns the number of parameters of the probability distribution.
getNumberOfPoints() - Method in class com.imsl.stat.KaplanMeierECDF
Retrieves the number of points in the empirical CDF
getNumberOfPredictors() - Method in class com.imsl.datamining.decisionTree.Tree
Returns the number of predictors used in the model.
getNumberOfPredictors() - Method in class com.imsl.datamining.PredictiveModel
Returns the number of predictors.
getNumberOfRegressors() - Method in class com.imsl.stat.RegressorsForGLM
Returns the number regressors.
getNumberOfRoots() - Method in class com.imsl.math.ZerosFunction
Returns the requested number of roots to be found.
getNumberOfRootsFound() - Method in class com.imsl.math.ZerosFunction
Returns the number of zeros found.
getNumberOfRows() - Method in class com.imsl.datamining.KohonenSOM
Returns the number of rows of the node grid.
getNumberOfRows() - Method in class com.imsl.datamining.PredictiveModel
Returns the number of rows in xy (observations).
getNumberOfRows() - Method in class com.imsl.io.MPSReader
Returns the number of rows in the constraint matrix.
getNumberOfRows() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the number of rows in the matrix.
getNumberOfRows() - Method in class com.imsl.math.SparseMatrix
Returns the number of rows in the matrix.
getNumberOfRowsMissing() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the number of rows of data encountered containing missing values (Double.NaN).
getNumberOfRowsMissing() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the number of rows of data in x that contain missing values in one or more specific columns of x.
getNumberOfSampleFolds() - Method in class com.imsl.datamining.CrossValidation
Returns the number of folds set for the cross validation selection.
getNumberOfSeries() - Method in class com.imsl.stat.TimeSeries
Returns the number of series stored in this TimeSeries object.
getNumberOfSets(double[], int[]) - Method in class com.imsl.datamining.decisionTree.DecisionTree
Returns the number of sets for a split.
getNumberOfSteps() - Method in class com.imsl.math.OdeAdamsGear
Returns the number of internal steps taken.
getNumberOfSurrogateSplits() - Method in class com.imsl.datamining.decisionTree.ALACART
Returns the number of surrogate splits.
getNumberOfSurrogateSplits() - Method in interface com.imsl.datamining.decisionTree.DecisionTreeSurrogateMethod
Indicates the number of surrogate splits.
getNumberOfSurrogateSplits() - Method in class com.imsl.datamining.decisionTree.Tree
Returns the number of surrogate splits searched for at each tree node.
getNumberOfThreads() - Method in class com.imsl.datamining.BootstrapAggregation
Returns the maximum number of java.lang.Thread instances that may be used for parallel processing.
getNumberOfThreads() - Method in class com.imsl.datamining.CrossValidation
Returns the maximum number of java.lang.Thread instances that may be used for parallel processing.
getNumberOfThreads() - Method in class com.imsl.datamining.KohonenSOMTrainer
Returns the number of java.lang.Thread instances used for parallel processing.
getNumberOfThreads() - Method in class com.imsl.datamining.neural.EpochTrainer
Gets the number of java.lang.Thread instances to use during stage I training.
getNumberOfThreads() - Method in class com.imsl.math.BoundedLeastSquares
Returns the number of java.lang.Thread instances used for parallel processing.
getNumberOfThreads() - Method in class com.imsl.math.MinConGenLin
Returns the number of java.lang.Thread instances used for parallel processing.
getNumberOfThreads() - Method in class com.imsl.math.MinConNLP
Returns the number of java.lang.Thread instances used for parallel processing.
getNumberOfThreads() - Method in class com.imsl.math.MinUnconMultiVar
Returns the number of java.lang.Thread instances used for parallel processing.
getNumberOfThreads() - Method in class com.imsl.math.NonlinLeastSquares
Returns the number of java.lang.Thread instances used for parallel processing.
getNumberOfThreads() - Method in class com.imsl.stat.AutoCorrelation
Returns the number of java.lang.Thread instances used for parallel processing.
getNumberOfTies() - Method in class com.imsl.stat.KolmogorovOneSample
Returns the number of ties in the data.
getNumberOfTransactions() - Method in class com.imsl.datamining.Itemsets
Returns an int indicating the number of transactions used to construct the itemsets.
getNumberOfUniquePredictorValues() - Method in class com.imsl.datamining.PredictiveModel
Returns an array containing the number of distinct values of each categorical or ordinal predictor found in the input data.
getNumberOfWeights() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the number of weights in the Network.
getNumberOfWeights() - Method in class com.imsl.datamining.neural.Network
Returns the number of weights in the Network.
getNumberRowsMissing() - Method in class com.imsl.stat.ProportionalHazards
Returns the number of rows of data in x that contain missing values in one or more specific columns of x.
getNumericFactor() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the numeric Cholesky factor.
getNumericFactor() - Method in class com.imsl.math.SparseCholesky
Returns the numeric Cholesky factor.
getNumericFactorizationMethod() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the method used in the numerical factorization of the permuted input matrix.
getNumericFactorizationMethod() - Method in class com.imsl.math.SparseCholesky
Returns the method used in the numerical factorization of the permuted input matrix.
getNumMissing() - Method in class com.imsl.stat.TimeSeries
Returns the number of missing values.
getNumPositiveDev() - Method in class com.imsl.stat.SignTest
Returns the number of positive differences.
getNumRowMissing() - Method in class com.imsl.stat.Covariances
Returns the total number of observations that contain any missing values (Double.NaN).
getNumZeroDev() - Method in class com.imsl.stat.SignTest
Returns the number of zero differences.
getNvalues() - Method in class com.imsl.stat.TableMultiWay.BalancedTable
Returns an array of length nKeys containing in its i-th element (i=0,1,...nKeys-1), the number of levels or categories of the i-th classification variable (column).
getObject(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(int, Map) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(String, Class) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object converted to the requested data type in the Java programming language.
getObject(int, Class) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object converted to the requested data type in the Java programming language.
getObject(String, Map) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(int) - Method in class com.imsl.io.FlatFile
Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObjective() - Method in class com.imsl.io.MPSReader
Returns the objective as a Row.
getObjectiveCoefficients() - Method in class com.imsl.io.MPSReader
Returns the coefficents of the objective row.
getObjectiveValue() - Method in class com.imsl.math.MinConGenLin
Returns the value of the objective function.
getObservations() - Method in class com.imsl.stat.Covariances
Returns the sum of the frequencies.
getObservationsLost() - Method in class com.imsl.stat.Difference
Returns the number of observations lost because of differencing the time series.
getObservedResponse() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the observed response for an observation.
getObsPerCluster(int) - Method in class com.imsl.stat.ClusterHierarchical
Returns the number of observations in each cluster.
getOffset() - Method in class com.imsl.chart.Text
Returns the offset.
getOmegaWeights() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the omega weights for the detected outliers.
getOneSidedPValue() - Method in class com.imsl.stat.KolmogorovOneSample
Probability of the statistic exceeding D under the null hypothesis of equality and against the one-sided alternative.
getOneSidedPValue() - Method in class com.imsl.stat.KolmogorovTwoSample
Probability of the statistic exceeding D under the null hypothesis of equality and against the one-sided alternative.
getOpen() - Method in class com.imsl.chart.HighLowClose
Gets the value of the attribute "Open".
getOptimalValue() - Method in class com.imsl.math.DenseLP
Returns the optimal value of the objective function.
getOptimalValue() - Method in class com.imsl.math.MinConNLP
Returns the value of the objective function.
getOptimalValue() - Method in class com.imsl.math.QuadraticProgramming
Returns the optimal value.
getOptimalValue() - Method in class com.imsl.math.SparseLP
Returns the optimal value of the objective function.
getOptimizedCriterion() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the optimized criterion.
getOptimumD() - Method in class com.imsl.stat.ARSeasonalFit
Returns the optimum values for d selected among the candidates in dInitial.
getOptimumModelOrder() - Method in class com.imsl.stat.AutoARIMA
Returns the order (p,0,q)times(0,d,0)_s of the optimum model.
getOptimumS() - Method in class com.imsl.stat.ARSeasonalFit
Returns the optimum values for s selected among the candidates in sInitial.
getOrbit() - Method in class com.imsl.chart3d.Chart3D
Returns the value of the "Orbit" attribute.
getOrder() - Method in class com.imsl.chart.Dendrogram
Convenience routine to get the "Order" attribute.
getOrder() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the order of the AR model selected with the minimum AIC.
getOrientation() - Method in class com.imsl.chart.Treemap
Gets the value of the "Orientation" attribute.
getOutlierFreeForecast() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns forecasts for the outlier free series.
getOutlierFreeForecast() - Method in class com.imsl.stat.AutoARIMA
Returns forecasts for the outlier free series.
getOutlierFreeSeries() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the outlier free series.
getOutlierFreeSeries() - Method in class com.imsl.stat.AutoARIMA
Returns the outlier free series.
getOutlierStatistics() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the outlier statistics.
getOutlierStatistics() - Method in class com.imsl.stat.AutoARIMA
Returns the outlier statistics.
getOutputLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the OutputLayer.
getOutputLayer() - Method in class com.imsl.datamining.neural.Network
Returns the OutputLayer.
getOutsideMarkers() - Method in class com.imsl.chart.BoxPlot
Returns the OutsideMarkers node.
getOutsideMarkers() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the array of outside markers.
getP() - Method in class com.imsl.stat.ANOVA
Returns the p-value.
getP() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the number of autoregressive terms in the ARMA model
getP() - Method in class com.imsl.stat.ChiSquaredTest
Returns the p-value for the chi-squared statistic.
getP() - Method in class com.imsl.stat.ContingencyTable
Returns the Pearson chi-squared p-value for independence of rows and columns.
getPaint() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Paint" attribute.
getPanel() - Method in class com.imsl.chart.JFrameChart
Returns the JPanelChart into which the chart is drawn.
getParamEstimatesCovariance() - Method in class com.imsl.stat.ARMA
Returns the covariances of parameter estimates.
getParameterLowerBounds() - Method in class com.imsl.stat.distributions.BetaPD
Returns the lower bounds for the two shape parameters of the beta distribution.
getParameterLowerBounds() - Method in class com.imsl.stat.distributions.GammaPD
Returns the lower bounds for the shape and scale parameters of the gamma distribution.
getParameterLowerBounds() - Method in class com.imsl.stat.distributions.NormalPD
Returns the lower bounds for the mean mu and standard deviation sigma.
getParameterLowerBounds() - Method in class com.imsl.stat.distributions.ProbabilityDistribution
Returns the lower bounds of the parameters.
getParameters() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the parameter estimates and associated statistics.
getParameters() - Method in class com.imsl.stat.GammaDistribution
Returns the current parameters of the gamma probability density function.
getParameters() - Method in class com.imsl.stat.LogNormalDistribution
Returns the current parameters of the lognormal probability density function
getParameters() - Method in class com.imsl.stat.NormalDistribution
Returns the current parameters of the normal probability density function.
getParameters() - Method in class com.imsl.stat.PoissonDistribution
Returns the current parameters of the Poisson probability density function.
getParameters() - Method in interface com.imsl.stat.ProbabilityDistribution
Returns the current parameters of the probability density function.
getParameterStatistics() - Method in class com.imsl.stat.ProportionalHazards
Returns the parameter estimates and associated statistics.
getParameterUpdates() - Method in class com.imsl.stat.FactorAnalysis
Returns the parameter updates.
getParameterUpperBounds() - Method in class com.imsl.stat.distributions.BetaPD
Returns the upper bounds for the two shape parameters of the beta distribution.
getParameterUpperBounds() - Method in class com.imsl.stat.distributions.GammaPD
Returns the upper bounds for the shape and scale parameters of the gamma distribution.
getParameterUpperBounds() - Method in class com.imsl.stat.distributions.NormalPD
Returns the upper bounds for the mean mu and standard deviation sigma.
getParameterUpperBounds() - Method in class com.imsl.stat.distributions.ProbabilityDistribution
Returns the upper bounds of the parameters.
getParent() - Method in class com.imsl.chart.ChartNode
Returns the parent of this node.
getParent() - Method in class com.imsl.chart3d.ChartNode3D
Returns the parent of this node.
getParentId() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the id of the parent node of the current node.
getPartialAutoCorrelations() - Method in class com.imsl.stat.AutoCorrelation
Returns the sample partial autocorrelation function of the stationary time series x.
getPartialCorrelationMatrix() - Method in class com.imsl.stat.PartialCovariances
Returns the partial correlation matrix.
getPartialCovarianceMatrix() - Method in class com.imsl.stat.PartialCovariances
Returns the partial covariance matrix.
getPartialDegreesOfFreedom() - Method in class com.imsl.stat.PartialCovariances
Returns the degrees of freedom in the test that the partial correlation (covariance) is zero.
getPDFGradient(double, double[]) - Method in class com.imsl.stat.distributions.NormalPD
Returns the analytic gradient of the normal pdf.
getPDFGradient(double, double[]) - Method in interface com.imsl.stat.distributions.PDFGradientInterface
Returns the gradient of the probability density function.
getPDFGradientApproximation(double, double[]) - Method in class com.imsl.stat.distributions.ProbabilityDistribution
Returns the approximate gradient of the probability density function, pdf.
getPDFHessian(double, double[]) - Method in class com.imsl.stat.distributions.NormalPD
Returns the analytic hessian matrix of the normal pdf evaluated at a point, x.
getPDFHessian(double, double[]) - Method in interface com.imsl.stat.distributions.PDFHessianInterface
Returns the hessian of the probability density function.
getPDFHessianApproximation(double, double[]) - Method in class com.imsl.stat.distributions.ProbabilityDistribution
Returns the approximate hessian of the probability density function, pdf.
getPercentageFactor() - Method in class com.imsl.math.NumericalDerivatives
Returns the percentage factor for differencing.
getPercentages() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Retrieves the cumulative percentages used for encoding and decoding.
getPercents() - Method in class com.imsl.stat.FactorAnalysis
Returns the cumulative percent of the total variance explained by each principal component.
getPerceptrons() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the Perceptrons in this Network.
getPerceptrons() - Method in class com.imsl.datamining.neural.Network
Returns an array containing the Perceptrons in the Network.
getPerformanceTuningParameters(int) - Method in class com.imsl.math.ComplexSuperLU
Returns a performance tuning parameter value.
getPerformanceTuningParameters(int) - Method in class com.imsl.math.SuperLU
Returns a performance tuning parameter value.
getPermutationMatrix() - Method in class com.imsl.math.ComplexLU
Returns the permutation matrix which results from the LU factorization of A.
getPermutationMatrix() - Method in class com.imsl.math.LU
Returns the permutation matrix which results from the LU factorization of A.
getPermute() - Method in class com.imsl.math.QR
Returns an integer vector containing information about the permutation of the elements of the matrix during pivoting.
getPhi() - Method in class com.imsl.stat.ContingencyTable
Returns phi.
getPieSlice() - Method in class com.imsl.chart.Pie
Returns the PieSlice objects.
getPieSlice(int) - Method in class com.imsl.chart.Pie
Returns a specified PieSlice.
getPivotGrowth() - Method in class com.imsl.math.ComplexSuperLU
Returns the reciprocal pivot growth factor flag.
getPivotGrowth() - Method in class com.imsl.math.SuperLU
Returns the reciprocal pivot growth factor flag.
getPooledVariance() - Method in class com.imsl.stat.NormTwoSample
Returns the Pooled variance for the two samples.
getPopulationTable(int[]) - Method in class com.imsl.stat.LifeTables
Compute a population table.
getPosition() - Method in class com.imsl.chart3d.ColormapLegend
Returns the position of the legend.
getPosition() - Method in class com.imsl.chart3d.PointLight
Returns the value of the "Position" attribute.
getPreconditionerSolves() - Method in class com.imsl.math.GenMinRes
Returns the total number of GMRES right preconditioner solves.
getPredictedClass() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the predicted class at the current node, for response variables of categorical type.
getPredictedClass() - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns the predicted classification for each training pattern.
getPredictedResponse() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the predicted response for an observation.
getPredictedVal() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the predicted value at the current node, for response variables of continuous type.
getPredictionError() - Method in class com.imsl.stat.KalmanFilter
Returns the one-step-ahead prediction error.
getPredictionInterval() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Prediction Interval of the predicted response for an observation.
getPredictions() - Method in class com.imsl.datamining.BootstrapAggregation
Returns the predicted values.
getPredictorIndexes() - Method in class com.imsl.datamining.PredictiveModel
Returns an array of indices into xy where the predictor variables reside.
getPredictorNumberOfValues() - Method in class com.imsl.datamining.decisionTree.Tree
Returns the number of distinct values of each predictor variable.
getPredictorType(int) - Method in class com.imsl.datamining.decisionTree.Tree
Returns the PredictiveModel.VariableType of a predictor variable.
getPredictorTypes() - Method in class com.imsl.datamining.PredictiveModel
Returns an array of VariableType objects that correspond to the predictor data types in xy.
getPreordering() - Method in class com.imsl.math.SparseLP
Returns the variant of the Minimum Degree Ordering (MDO) algorithm used in the preordering of the normal equations or augmented system matrix.
getPresolve() - Method in class com.imsl.math.SparseLP
Returns the presolve option.
getPrimalInfeasibility() - Method in class com.imsl.math.SparseLP
Returns the primal infeasibility of the solution.
getPrimalInfeasibilityTolerance() - Method in class com.imsl.math.SparseLP
Returns the primal infeasibility tolerance.
getPrimalSolution() - Method in class com.imsl.math.DenseLP
Returns the solution x of the linear programming problem.
getPrintLevel() - Method in class com.imsl.datamining.BootstrapAggregation
Returns the current print level.
getPrintLevel() - Method in class com.imsl.datamining.PredictiveModel
Returns the current print level.
getPrintLevel() - Method in class com.imsl.math.SparseLP
Returns the print level.
getPrior() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the prior probabilities.
getPriorProbabilities() - Method in class com.imsl.datamining.PredictiveModel
Returns an array containing the prior probabilities.
getProbabilities() - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns the predicted classification probabilities for each target class.
getProbability() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the posterior probabilities for each observation.
getProduct() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the inverse of the Hessian times the gradient vector computed at the input parameter estimates.
getProducts() - Method in class com.imsl.math.GenMinRes
Returns the total number of GMRES matrix-vector products used.
getPsiWeights() - Method in class com.imsl.stat.ARMA
Returns the psi weights of the infinite order moving average form of the model.
getPsiWeights() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the psi weights used for calculating forecasts from the infinite order moving average form of the ARMA model.
getPsiWeights() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the psi weights of the infinite order moving average form of the model.
getPsiWeights() - Method in class com.imsl.stat.AutoARIMA
Returns the psi weights of the infinite order moving average form of the model.
getPValue(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests
Returns the p-value for the two-sided test.
getPValue(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests
Returns the p-value for the two-sided test H_0 : {
  beta} = 0 vs.
getPValues() - Method in class com.imsl.stat.PartialCovariances
Calculates the p-values for testing the null hypothesis that the associated partial covariance/correlation is zero.
getQ() - Method in class com.imsl.math.QR
Returns the orthogonal or unitary matrix Q.
getQ() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the number of moving average terms in the ARMA model
getQ() - Method in class com.imsl.stat.EmpiricalQuantiles
Returns the empirical quantiles.
getR() - Method in class com.imsl.math.Cholesky
Returns the R matrix that results from the Cholesky factorization.
getR() - Method in class com.imsl.math.QR
Returns the upper trapezoidal matrix R.
getR() - Method in class com.imsl.stat.ANCOVA
Returns the R matrix from the QR decomposition.
getR() - Method in class com.imsl.stat.LinearRegression
Returns a copy of the R matrix.
getR() - Method in class com.imsl.stat.NonlinearRegression
Returns a copy of the R matrix.
getRadialFunction() - Method in class com.imsl.math.RadialBasis
Returns the radial function.
getRadius(int) - Method in class com.imsl.math.ZeroPolynomial
Returns an a-posteriori absolute error bound on the root.
getRandom() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the random number generator used to perturb the stage 1 guesses.
getRandomObject() - Method in class com.imsl.datamining.PredictiveModel
Returns the random object being used in the permutation of the observations.
getRandomSampleIndicies() - Method in class com.imsl.datamining.neural.EpochTrainer
Gets the random number generators used to select random training patterns in stage 1.
getRangeOfX() - Method in class com.imsl.stat.distributions.ProbabilityDistribution
Returns the proper range of the random variable having the current probability distribution.
getRank() - Method in class com.imsl.math.QR
Returns the rank of the matrix used to construct this instance.
getRank() - Method in class com.imsl.math.SVD
Returns the rank of the matrix used to construct this instance.
getRank() - Method in class com.imsl.stat.KalmanFilter
Returns the rank of the variance-covariance matrix for all the observations.
getRank() - Method in class com.imsl.stat.LinearRegression
Returns the rank of the matrix.
getRank() - Method in class com.imsl.stat.NonlinearRegression
Returns the rank of the matrix.
getRanks(double[]) - Method in class com.imsl.stat.Ranks
Gets the rank for each observation.
getRbar() - Method in class com.imsl.chart.qc.XbarR
Returns the value of the "Rbar" attribute, the mean of the ranges for a series of samples.
getReciprocalPivotGrowthFactor() - Method in class com.imsl.math.ComplexSuperLU
Returns the reciprocal pivot growth factor.
getReciprocalPivotGrowthFactor() - Method in class com.imsl.math.SuperLU
Returns the reciprocal pivot growth factor.
getRef(int) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Ref object in the Java programming language.
getRef(String) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Ref object in the Java programming language.
getReference() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Reference" attribute.
getRegressors() - Method in class com.imsl.stat.RegressorsForGLM
Returns the regressor array.
getRelativeBackwardError() - Method in class com.imsl.math.ComplexSuperLU
Returns the componentwise relative backward error of the solution vector.
getRelativeBackwardError() - Method in class com.imsl.math.SuperLU
Returns the componentwise relative backward error of the solution vector.
getRelativeError(double) - Method in class com.imsl.math.ConjugateGradient
Returns the relative error used for stopping the algorithm.
getRelativeError() - Method in class com.imsl.math.GenMinRes
Returns the stopping tolerance.
getRelativeError() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the relative error used for the METHOD_OF_MOMENTS and LEAST_SQARES estimation methods.
getRelativeErrorTolerances() - Method in class com.imsl.math.FeynmanKac
Returns relative error tolerances.
getRelativeH() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the value for relative h.
getRelativeOptimalityTolerance() - Method in class com.imsl.math.SparseLP
Returns the relative optimality tolerance.
getResidual() - Method in class com.imsl.stat.ARMA
Returns the residuals.
getResidual() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the residuals.
getResidual() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Residual for an observation.
getResidualNorm() - Method in class com.imsl.math.BoundedVariableLeastSquares
Returns the euclidean norm of the residual vector, |Ax-b|^2.
getResidualNorm() - Method in class com.imsl.math.GenMinRes
Returns the final residual norm, {Vert b-Ax Vert}_2 .
getResidualNorm() - Method in class com.imsl.math.NonNegativeLeastSquares
Returns the euclidean norm of the residual vector, |Ax-b|^2.
getResiduals() - Method in class com.imsl.math.BoundedLeastSquares
Returns the residuals at the approximate solution.
getResiduals() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the current values of the vector of residuals.
getResiduals() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the current values of the vector of residuals.
getResiduals() - Method in class com.imsl.stat.AutoARIMA
Returns the residuals.
getResidualStandardError() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the residual standard error of the outlier free series.
getResidualStandardError() - Method in class com.imsl.stat.AutoARIMA
Returns the residual standard error of the outlier free series.
getResidualUpdating() - Method in class com.imsl.math.GenMinRes
Returns the residual updating method to be used.
getResponseColumn() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the column index of x containing the response time for each observation.
getResponseColumn() - Method in class com.imsl.stat.ProportionalHazards
Returns the column index of x containing the response time for each observation.
getResponseColumnIndex() - Method in class com.imsl.datamining.PredictiveModel
Returns the column index in xy containing the response variable.
getResponseType() - Method in class com.imsl.datamining.decisionTree.Tree
Returns the PredictiveModel.VariableType of the response variable.
getResponseVariableAverage() - Method in class com.imsl.datamining.PredictiveModel
Returns the weighted average value of the response variable.
getResponseVariableMostFrequentClass() - Method in class com.imsl.datamining.PredictiveModel
Returns the most frequent value of the response variable.
getResponseVariableType() - Method in class com.imsl.datamining.PredictiveModel
Returns the variable type of the response variable.
getRightEndTangent() - Method in class com.imsl.math.CsTCB
Returns the value of the tangent at the rightmost endpoint.
getRightSons() - Method in class com.imsl.chart.Dendrogram
Convenience routine to get the "RightSons" attribute.
getRiskStandardErrors() - Method in class com.imsl.datamining.CrossValidation
Returns the estimated standard errors for the risk values.
getRiskValues() - Method in class com.imsl.datamining.CrossValidation
Returns the vector of risk values.
getRoot(int) - Method in class com.imsl.math.ZeroPolynomial
Returns a zero of the polynomial.
getRoots() - Method in class com.imsl.math.ZeroPolynomial
Returns the zeros of the polynomial.
getRow() - Method in class com.imsl.io.AbstractFlatFile
Retrieves the current row number.
getRow(int) - Method in class com.imsl.io.MPSReader
Returns a row of the constraint matrix or a free row.
getRow() - Method in class com.imsl.stat.Dissimilarities
Returns a boolean indicating whether distances are computed between rows or columns of x.
getRowCoefficients(int) - Method in class com.imsl.io.MPSReader
Returns the coefficents of a row.
getRowId(int) - Method in class com.imsl.io.FlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a java.sql.RowId object in the Java programming language.
getRowId(String) - Method in class com.imsl.io.FlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a java.sql.RowId object in the Java programming language.
getRSquared() - Method in class com.imsl.stat.ANOVA
Returns the R-squared (in percent).
getS() - Method in class com.imsl.math.SVD
Returns the singular values.
getSafePixel(Color) - Static method in class com.imsl.chart.WebSafeImageFilter
Returns the Web-safe color nearest the given color.
getSampleSize() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the value of the attribute "SampleSize".
getSampleSizeProportion() - Method in class com.imsl.datamining.GradientBoosting
Returns the current setting of the sample size proportion.
getSampleStandardDeviation() - Method in class com.imsl.stat.Summary
Returns the sample standard deviation.
getSampleVariance() - Method in class com.imsl.stat.Summary
Returns the sample variance.
getSavageScores(double[]) - Method in class com.imsl.stat.Ranks
Gets the Savage scores (the expected value of exponential order statistics).
getScale() - Method in class com.imsl.math.ODE
Returns the scaling factor.
getScaleFont() - Method in class com.imsl.chart.Draw
Returns the factor by which fonts are to be scaled.
getScaleParameter() - Method in class com.imsl.stat.GammaDistribution
Returns the maximum-likelihood estimate found for the gamma scale parameter.
getScalingFactors() - Method in class com.imsl.math.NumericalDerivatives
Returns the scaling factors for the y values.
getScalingOption() - Method in class com.imsl.stat.Dissimilarities
Returns the scaling option.
getScreenAxis() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ScreenAxis" attribute.
getScreenSize() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ScreenSize" attribute.
getScreenViewport() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Viewport" attribute scaled by the screen size.
getSeriesValues() - Method in class com.imsl.stat.TimeSeries
Returns the values associated with the time series.
getSeriesValues(int) - Method in class com.imsl.stat.TimeSeries
 
getShapeParameter() - Method in class com.imsl.stat.GammaDistribution
Returns the maximum-likelihood estimate found for the gamma shape parameter.
getShapiroWilkW() - Method in class com.imsl.stat.NormalityTest
Returns the Shapiro-Wilk W statistic for the Shapiro-Wilk W test.
getShort(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a short in the Java programming language.
getShort(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a short in the Java programming language.
getShrinkageParameter() - Method in class com.imsl.datamining.GradientBoosting
Returns the current shrinkage parameter.
getSigma() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the standard deviation of the data.
getSigma() - Method in class com.imsl.stat.GARCH
Returns the estimated value of sigma squared.
getSInitial() - Method in class com.imsl.stat.ARSeasonalFit
Returns the the candidate values for s to evaluate.
getSize() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Size" attribute.
getSize(Text) - Method in class com.imsl.chart.Draw
Returns the size of the bounding box for a text object.
getSize() - Method in class com.imsl.chart.JspBean
Returns the size of the generated image.
getSkewness() - Method in class com.imsl.stat.Summary
Returns the skewness.
getSkip() - Method in class com.imsl.stat.FaureSequence
Returns the number of points skipped at the beginning of the sequence.
getSkipWeekends() - Method in class com.imsl.chart.ChartNode
Returns the value of the "SkipWeekends" attribute.
getSlackValue() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the slack value.
getSmallestCPRatio() - Method in class com.imsl.math.SparseLP
Returns the ratio of the smallest complementarity product to the average.
getSmallestDiagonalElement() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the smallest diagonal element of the Cholesky factor.
getSmallestDiagonalElement() - Method in class com.imsl.math.SparseCholesky
Returns the smallest diagonal element of the Cholesky factor.
getSmoothedSeries() - Method in class com.imsl.stat.HoltWintersExponentialSmoothing
Returns the fitted series values.
getSolution() - Method in class com.imsl.math.BoundedLeastSquares
Returns the solution.
getSolution() - Method in class com.imsl.math.BoundedVariableLeastSquares
Returns the solution to the problem.
getSolution() - Method in class com.imsl.math.MinConGenLin
Returns the computed solution.
getSolution() - Method in class com.imsl.math.MinConNLP
Returns the last computed solution.
getSolution() - Method in class com.imsl.math.NonNegativeLeastSquares
Returns the solution to the problem, x.
getSolution() - Method in class com.imsl.math.QuadraticProgramming
Returns the solution.
getSolution() - Method in class com.imsl.math.SparseLP
Returns the solution x of the linear programming problem.
getSolveMethod() - Method in class com.imsl.math.OdeAdamsGear
Returns the method for solving the formula equations.
getSpline() - Method in class com.imsl.math.BSpline
Returns a Spline representation of the B-spline.
getSplineCoefficients() - Method in class com.imsl.math.FeynmanKac
Returns the coefficients of the Hermite quintic splines that represent an approximate solution of the Feynman-Kac PDE.
getSplineCoefficientsPrime() - Method in class com.imsl.math.FeynmanKac
Returns the first derivatives of the Hermite quintic spline coefficients that represent an approximate solution of the Feynman-Kac PDE.
getSplineValue(double[], double[], int) - Method in class com.imsl.math.FeynmanKac
Evaluates for time value 0 or a time value in tGrid the derivative of the Hermite quintic spline interpolant at evaluation points within the range of xGrid.
getSplitMergedCategoriesSigLevel() - Method in class com.imsl.datamining.decisionTree.CHAID
Returns the significance level for splitting previously merged categories.
getSplitVariableSelectionCriterion() - Method in class com.imsl.datamining.decisionTree.QUEST
Returns the significance level for split variable selection.
getSplitVariableSignificanceLevel() - Method in class com.imsl.datamining.decisionTree.CHAID
Returns the significance level for split variable selection.
getSpread() - Method in class com.imsl.datamining.neural.ScaleFilter
Retrieves the measure of spread to be used during scaling.
getSQLXML(int) - Method in class com.imsl.io.FlatFile
Retrieves the value of the designated column in the current row of this ResultSet as a java.sql.SQLXML object in the Java programming language.
getSQLXML(String) - Method in class com.imsl.io.FlatFile
Retrieves the value of the designated column in the current row of this ResultSet as a java.sql.SQLXML object in the Java programming language.
getSSE() - Method in class com.imsl.stat.NonlinearRegression
Returns the sums of squares for error.
getSSResidual() - Method in class com.imsl.stat.ARMA
Returns the sum of squares of the random shock.
getStage1Trainer() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the stage 1 trainer.
getStage2Trainer() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the stage 1 trainer.
getStandardDeviation() - Method in class com.imsl.stat.LogNormalDistribution
Returns the lognormal probability distribution standard deviation parameter.
getStandardDeviation() - Method in class com.imsl.stat.NormalDistribution
Returns the population standard deviation.
getStandardDeviation() - Method in class com.imsl.stat.Summary
Returns the population standard deviation.
getStandardDeviations(double[][], int[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns a table of standard deviations for each continuous attribute in continuousData segmented by the target classes in classificationData.
getStandardError(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests
Returns the estimated standard error for a coefficient estimate.
getStandardError(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests
Returns the estimated standard error for a coefficient estimate.
getStandardErrors(int) - Method in class com.imsl.stat.AutoCorrelation
Returns the standard errors of the autocorrelations of the time series x.
getStandardErrors(int) - Method in class com.imsl.stat.CrossCorrelation
Returns the standard errors of the cross-correlations between the time series x and y.
getStandardErrors() - Method in class com.imsl.stat.distributions.MaximumLikelihoodEstimation
Returns the approximate standard errors of the maximum likelihood estimates.
getStandardErrors() - Method in class com.imsl.stat.FactorAnalysis
Returns the estimated asymptotic standard errors of the eigenvalues.
getStandardErrors() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns Greenwood's estimated standard errors.
getStandardizedResidual() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Standardized Residual for an observation.
getStartDate() - Method in class com.imsl.stat.TimeSeries
Returns the starting date of the time series.
getStatement() - Method in class com.imsl.io.AbstractFlatFile
Returns the Statement object that produced this ResultSet object.
getStateVector() - Method in class com.imsl.stat.KalmanFilter
Returns the estimated state vector at time k + 1 given the observations through time k.
getStatistics() - Method in class com.imsl.chart.BoxPlot
Returns an array of BoxPlot.Statistics objects, one for each set of observations.
getStatistics(int) - Method in class com.imsl.chart.BoxPlot
Returns a BoxPlot.Statistics for a set of observations.
getStatistics() - Method in class com.imsl.stat.ContingencyTable
Returns the statistics associated with this table.
getStatistics() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns statistics.
getStatistics() - Method in class com.imsl.stat.FactorAnalysis
Returns statistics.
getStatistics() - Method in class com.imsl.stat.SelectionRegression
Returns a new Statistics object.
getStatistics() - Method in class com.imsl.stat.WilcoxonRankSum
Returns the statistics.
getStatus() - Method in class com.imsl.math.NumericalDerivatives
Returns status information.
getStatus(int) - Method in class com.imsl.math.ZeroPolynomial
Returns the error status of a root.
getStdDev() - Method in class com.imsl.stat.NormOneSample
Returns the standard deviation of the sample.
getStdDevX() - Method in class com.imsl.stat.NormTwoSample
Returns the standard deviation of the first sample.
getStdDevY() - Method in class com.imsl.stat.NormTwoSample
Returns the standard deviation of the second sample.
getStepControlMethod() - Method in class com.imsl.math.FeynmanKac
Returns the step control method used in the integration of the Feynman-Kac PDE.
getStratumColumn() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the column index of x containing the stratum number for each observation.
getStratumColumn() - Method in class com.imsl.stat.ProportionalHazards
Returns the column index of x containing the stratum number for each observation.
getStratumNumbers() - Method in class com.imsl.stat.ProportionalHazards
Returns the stratum number used for each observation.
getStratumRatio() - Method in class com.imsl.stat.ProportionalHazards
Returns the ratio at which a stratum is split into two strata.
getString() - Method in class com.imsl.chart.Text
Gets the string for this Text object.
getString(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a String in the Java programming language.
getString(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a String in the Java programming language.
getStringAttribute(String) - Method in class com.imsl.chart.AbstractChartNode
Convenience routine to get a String-valued attribute.
getSumOfSquares() - Method in class com.imsl.stat.HoltWintersExponentialSmoothing
Returns the sum of squares of the one step ahead forecast errors.
getSumOfSquares() - Method in class com.imsl.stat.KalmanFilter
Returns the generalized sum of squares.
getSumOfSquaresForError() - Method in class com.imsl.stat.ANOVA
Returns the sum of squares for error.
getSumOfSquaresForModel() - Method in class com.imsl.stat.ANOVA
Returns the sum of squares for model.
getSumOfWeights() - Method in class com.imsl.stat.Covariances
Returns the sum of the weights of all observations.
getSupport() - Method in class com.imsl.datamining.AssociationRule
Support for the Z, X, and Y components of the association rule.
getSupport(int) - Method in class com.imsl.datamining.Itemsets
Returns the support determined for a particular itemset.
getSurfaceType() - Method in class com.imsl.chart3d.Surface
Returns the attribute "SurfaceType".
getSurrogateInfo() - Method in class com.imsl.datamining.decisionTree.ALACART
Returns the surrogate split information.
getSurrogateInfo() - Method in interface com.imsl.datamining.decisionTree.DecisionTreeSurrogateMethod
Returns the surrogate split information.
getSurrogateInfo(int) - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns a value from the surrogate split information array.
getSurrogateInfo() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns the surrogate split information array.
getSurvivalProbabilities() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the estimated survival probabilities.
getSwept() - Method in class com.imsl.stat.StepwiseRegression
Returns an array containing information indicating whether or not a particular variable is in the model.
getSymbolicFactor() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the symbolic Cholesky factor.
getSymbolicFactor() - Method in class com.imsl.math.SparseCholesky
Returns the symbolic Cholesky factor.
getSymmetricMode() - Method in class com.imsl.math.ComplexSuperLU
Returns the symmetric mode flag.
getSymmetricMode() - Method in class com.imsl.math.SuperLU
Returns the symmetric mode flag.
getTable() - Method in class com.imsl.stat.TableMultiWay.BalancedTable
Returns an array containing the frequencies for each variable.
getTable() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable
Returns the frequency for each cell.
getTauStatistics() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the t value for each detected outlier.
getTerminalNodeIndicators() - Method in class com.imsl.datamining.decisionTree.Tree
Returns the terminal node indicator array.
getTerminationCriterion() - Method in class com.imsl.math.MinConNLP
Returns the reason the solve step terminated.
getTerminationStatus() - Method in class com.imsl.math.SparseLP
Returns the termination status for the problem.
getTestClassFittedValues() - Method in class com.imsl.datamining.GradientBoosting
Returns the fitted values {f(x_i)} for a categorical response variable with two or more levels on the test data.
getTestClassProbabilities() - Method in class com.imsl.datamining.GradientBoosting
Returns the predicted probabilities on the test data for a categorical response variable.
getTestEffects() - Method in class com.imsl.stat.ANOVAFactorial
Returns statistics relating to the sums of squares for the effects in the model.
getTestFittedValues() - Method in class com.imsl.datamining.GradientBoosting
Returns the fitted values {f(x_i)} for a continuous response variable after gradient boosting on the test data.
getTestLossValue() - Method in class com.imsl.datamining.GradientBoosting
Returns the loss function value on the test data.
getTestStatistic() - Method in class com.imsl.stat.KolmogorovOneSample
Returns D = max(D^{+}, D^{-}).
getTestStatistic() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns D = max(D^{+}, D^{-}).
getText() - Method in class com.imsl.chart.Annotation
Gets the Text for this Annotation object.
getTextAngle() - Method in class com.imsl.chart.ChartNode
Returns the value of the "TextAngle" attribute.
getTextColor() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "TextColor" attribute.
getTextColor() - Method in class com.imsl.chart.ChartNode
Returns the value of the "TextColor" attribute.
getTextFormat() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "TextFormat" attribute.
getTheta() - Method in class com.imsl.stat.PoissonDistribution
Returns the mean number of successes in a given time period of the Poisson probability distribution.
getTickInterval() - Method in class com.imsl.chart.Axis1D
Retrieves the tick interval.
getTickInterval() - Method in class com.imsl.chart.AxisR
Retrieves the tick interval.
getTickInterval() - Method in class com.imsl.chart3d.Axis3D
Retrieves the tick interval.
getTickLength() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "TickLength" attribute.
getTicks() - Method in class com.imsl.chart.Axis1D
Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart.AxisR
Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart.AxisTheta
Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart3d.Axis3D
Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart3d.ColormapLegend
Returns the value of the "Ticks" attribute, if set.
getTiesOption() - Method in class com.imsl.stat.ProportionalHazards
Returns the method used for handling ties.
getTime(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTime(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTime(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTime(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTimeBarrier() - Method in class com.imsl.math.FeynmanKac
Returns the barrier set for integration in the time direction.
getTimes() - Method in class com.imsl.stat.KaplanMeierECDF
Retrieves the time values where the step function CDF jumps to a greater value.
getTimeSeries() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the time series used for estimating the minimum AIC and the autoregressive coefficients.
getTimeSeries() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the time series used to construct ARMAMaxLikelihood.
getTimeSeries() - Method in class com.imsl.stat.ARSeasonalFit
Returns the time series.
getTimestamp(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.
getTimestamp(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object.
getTimestamp(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.
getTimestamp(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.
getTimeZone() - Method in class com.imsl.stat.TimeSeries
Returns the time zone of the time series.
getTimeZoneOffset() - Method in class com.imsl.stat.TimeSeries
Returns the number of hours (+ or -) from GMT of the time zone associated with the time series.
getTimsacAR() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final auto regressive parameter estimates at the optimum AIC estimated by the original TIMSAC routine (UNIMAR).
getTimsacConstant() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the estimate for the constant parameter in the ARMA series.
getTimsacVariance() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final estimate for the innovation variance calculated by the TIMSAC automatic AR modeling routine (UNIMAR).
getTitle() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Title" attribute.
getTitle() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Title" attribute.
getTo() - Method in class com.imsl.datamining.neural.Link
Returns the destination Node for this Link.
getTolerance() - Method in class com.imsl.chart.DrawMap
Get the minimum distance that an event can be from a point or a line and still be considered a hit.
getTolerance() - Method in class com.imsl.chart.DrawPick
Get the minimum distance that an event can be from a point or a line and still be considered a hit.
getTolerance() - Method in class com.imsl.math.MinConNLP
Returns the desired precision of the solution.
getTolerance() - Method in class com.imsl.math.ODE
Returns the error tolerance.
getTolerance() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the tolerance for the convergence algorithm.
getToolTip() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ToolTip" attribute.
getTotalDegreesOfFreedom() - Method in class com.imsl.stat.ANOVA
Returns the total degrees of freedom.
getTotalMissing() - Method in class com.imsl.stat.ANOVA
Returns the total number of missing values.
getTotalMissing() - Method in class com.imsl.stat.EmpiricalQuantiles
Returns the total number of missing values.
getTotalNumberOfFailures(double) - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the total number failing in the group for the specified group value.
getTotalSumOfSquares() - Method in class com.imsl.stat.ANOVA
Returns the total sum of squares.
getTotalWeight() - Method in class com.imsl.datamining.PredictiveModel
Returns the sum of the active case weights.
getTrainingErrors() - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns a table of classification errors of non-missing classifications for each target classification plus the overall total of classification errors.
getTrainingIterations() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the number of iterations used during training.
getTransform() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Transform" attribute.
getTransform() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Retrieves the transform flag used for encoding and decoding.
getTransformedTimeSeries() - Method in class com.imsl.stat.ARSeasonalFit
Returns the transformed series, W_t(s,d).
getTransformType() - Method in class com.imsl.stat.ClusterHierarchical
Returns the type of transformation.
getTreemapLegend() - Method in class com.imsl.chart.Treemap
Returns the treemap legend.
getTStatistic(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests
Returns the t-statistic for the test that the i-th coefficient is zero.
getTStatistic(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests
Returns the student-t test statistic for testing the i-th coefficient equal to zero ({beta}_{index} = 0).
getTTest() - Method in class com.imsl.stat.NormOneSample
Returns the test statistic associated with the t test.
getTTest() - Method in class com.imsl.stat.NormTwoSample
Returns the test statistic for the Satterthwaite's approximation.
getTTestDF() - Method in class com.imsl.stat.NormOneSample
Returns the degrees of freedom associated with the t test for the mean.
getTTestDF() - Method in class com.imsl.stat.NormTwoSample
Returns the degrees of freedom for the Satterthwaite's approximation for t-test for either equal or unequal variances, depending on the value set by setUnequalVariances.
getTTestP() - Method in class com.imsl.stat.NormOneSample
Returns the probability associated with the t test of a larger t in absolute value.
getTTestP() - Method in class com.imsl.stat.NormTwoSample
Returns the approximate probability of a larger t for the Satterthwaite's approximation for equal or unequal variances.
getTukeyScores(double[]) - Method in class com.imsl.stat.Ranks
Gets the Tukey version of normal scores for each observation.
getTwoSidedPValue() - Method in class com.imsl.stat.KolmogorovOneSample
Probability of the statistic exceeding D under the null hypothesis of equality and against the two-sided alternative.
getTwoSidedPValue() - Method in class com.imsl.stat.KolmogorovTwoSample
Probability of the statistic exceeding D under the null hypothesis of equality and against the two-sided alternative.
getType() - Method in class com.imsl.chart.Axis1D
Returns the axis type.
getType() - Method in class com.imsl.chart.Grid
Returns the axis type.
getType() - Method in class com.imsl.chart3d.Axis3D
Returns the axis type.
getType() - Method in class com.imsl.io.AbstractFlatFile
Returns the type of this ResultSet object.
getTypeVariable(int) - Method in class com.imsl.io.MPSReader
Returns the type of a variable.
getU() - Method in class com.imsl.math.ComplexLU
Returns the unit upper triangular portion of the LU factorization of A.
getU() - Method in class com.imsl.math.LU
Returns the unit upper triangular portion of the LU factorization of A.
getU() - Method in class com.imsl.math.SVD
Returns the left singular vectors.
getUnbalancedTable() - Method in class com.imsl.stat.TableMultiWay
Returns an object containing the unbalanced table.
getUnion(Itemsets, Itemsets) - Static method in class com.imsl.datamining.Apriori
Return the union of two sets of itemsets.
getUp() - Method in class com.imsl.chart.Candlestick
Returns the CandlestickItem for up days.
getUpperAdjacentValue() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the lower adjacent value.
getUpperBound(int) - Method in class com.imsl.io.MPSReader
Returns the upper bound for a variable.
getUpperBound() - Method in class com.imsl.math.SparseLP
Returns the upper bound on the variables.
getUpperCICommonVariance() - Method in class com.imsl.stat.NormTwoSample
Returns the upper confidence limits for the common, or pooled, variance.
getUpperCIDiff() - Method in class com.imsl.stat.NormTwoSample
Returns the upper confidence limit for the mean of the first population minus the mean of the second for equal or unequal variances depending on the value set by setUnequalVariances.
getUpperCIMean() - Method in class com.imsl.stat.NormOneSample
Returns the upper confidence limit for the mean.
getUpperCIRatioVariance() - Method in class com.imsl.stat.NormTwoSample
Returns the approximate upper confidence limit for the ratio of the variance of the first population to the second.
getUpperCIVariance() - Method in class com.imsl.stat.NormOneSample
Returns the upper confidence limits for the variance.
getUpperControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the upper control limit.
getUpperLimit() - Method in class com.imsl.math.SparseLP
Returns the upper limit of the constraints that have both a lower and an upper bound.
getUpperQuartile() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the upper quartile value.
getUpperRange(int) - Method in class com.imsl.io.MPSReader
Returns the upper range value for a constraint equation.
getURL(String) - Method in class com.imsl.io.AbstractFlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a java.net.URL object.
getURL(int) - Method in class com.imsl.io.AbstractFlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a java.net.URL object.
getUseBackPropagation() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the use back propagation setting.
getV() - Method in class com.imsl.math.SVD
Returns the right singular vectors.
getValue() - Method in class com.imsl.chart.qc.ControlLimit
Returns the value of this control limit line.
getValue() - Method in class com.imsl.datamining.neural.InputNode
Returns the value of this node.
getValue() - Method in class com.imsl.datamining.neural.OutputPerceptron
Returns the value of the OutputPerceptron determined using the current network state and inputs.
getValue() - Method in class com.imsl.io.MPSReader.Element
Returns the value of the element.
getValues() - Method in class com.imsl.math.Eigen
Returns the eigenvalues of a matrix of type double.
getValues() - Method in class com.imsl.math.SymEigen
Returns the eigenvalues
getValues() - Method in class com.imsl.stat.FactorAnalysis
Returns the eigenvalues.
getValues() - Method in class com.imsl.stat.TableMultiWay.BalancedTable
Returns the values of the classification variables.
getVanDerWaerdenScores(double[]) - Method in class com.imsl.stat.Ranks
Gets the Van der Waerden version of normal scores for each observation.
getVarCov() - Method in class com.imsl.stat.distributions.MaximumLikelihoodEstimation
Returns the approximate variance-covariance matrix of the maximum likelihood estimates.
getVarCovAdjustedMeans() - Method in class com.imsl.stat.ANCOVA
Returns a matrix containing the estimated variances and covariances for the adjusted means assuming parallelism.
getVarCovarMatrix() - Method in class com.imsl.stat.GARCH
Returns the variance-covariance matrix.
getVarCovarMatrix() - Method in class com.imsl.stat.HoltWintersExponentialSmoothing
Returns the variance-covariance matrix of the smoothing parameters estimated by minimizing the mean squared forecast error.
getVarCovCoefficients() - Method in class com.imsl.stat.ANCOVA
Returns a matrix containing the estimated variances and covariances for the coefficients returned using getModelCoefficients.
getVariableType() - Method in class com.imsl.datamining.PredictiveModel
Returns an array containing the variable types in xy.
getVariance() - Method in class com.imsl.stat.ARMA
Returns the variance of the time series z.
getVariance() - Method in class com.imsl.stat.AutoCorrelation
Returns the variance of the time series x.
getVariance() - Method in class com.imsl.stat.Summary
Returns the population variance.
getVarianceCovarianceMatrix() - Method in class com.imsl.stat.ProportionalHazards
Returns the estimated asymptotic variance-covariance matrix of the parameters.
getVariances() - Method in class com.imsl.stat.FactorAnalysis
Gets the unique variances.
getVarianceX() - Method in class com.imsl.stat.CrossCorrelation
Returns the variance of time series x.
getVarianceX() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the variances of the channels of x.
getVarianceY() - Method in class com.imsl.stat.CrossCorrelation
Returns the variance of time series y.
getVarianceY() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the variances of the channels of y.
getVectorProducts() - Method in class com.imsl.math.GenMinRes
Returns the user-supplied functions for the inner product and, optionally, the norm used in the Gram-Schmidt implementations.
getVectors() - Method in class com.imsl.math.Eigen
Returns the eigenvectors.
getVectors() - Method in class com.imsl.math.SymEigen
Return the eigenvectors of a symmetric matrix of type double.
getVectors() - Method in class com.imsl.stat.FactorAnalysis
Returns the eigenvectors.
getViewPlatformTransformation(Transform3D) - Method in class com.imsl.chart3d.Chart3D
Sets the transformation for the view platform.
getViewport() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Viewport" attribute.
getViewport() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Viewport" attribute.
getViolation() - Method in class com.imsl.math.SparseLP
Returns the violation of the variable bounds.
getVirtualUniverse() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Universe" attribute.
getVisibleFaces() - Method in class com.imsl.chart3d.AxisBox
Returns the flag indicating which faces of the box are to be drawn.
getWarning() - Static method in class com.imsl.Warning
Gets the WarningObject.
getWarnings() - Method in class com.imsl.io.AbstractFlatFile
Returns the first warning reported by calls on this ResultSet object.
getWbar() - Method in class com.imsl.chart.qc.XbarS
Returns the value of the "Wbar" attribute, the within sample variation for a series of samples.
getWeight() - Method in class com.imsl.datamining.neural.Link
Returns the weight for this Link.
getWeights(int, int) - Method in class com.imsl.datamining.KohonenSOM
Returns the weights of the node at (i, j) in the node grid.
getWeights() - Method in class com.imsl.datamining.KohonenSOM
Returns the weights of the nodes.
getWeights() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the weights for the Links in this network.
getWeights() - Method in class com.imsl.datamining.neural.Network
Returns the weights.
getWeights() - Method in class com.imsl.datamining.PredictiveModel
Returns an array containing the case weights.
getWhiskers() - Method in class com.imsl.chart.BoxPlot
Returns the Whiskers node.
getWindow() - Method in class com.imsl.chart.Axis1D
Returns the window for an Axis1D.
getWindow() - Method in class com.imsl.chart.AxisR
Returns the Window attribute.
getWindow() - Method in class com.imsl.chart.AxisTheta
Returns the window for an AxisTheta.
getWindow() - Method in class com.imsl.chart3d.Axis3D
Returns the window for an Axis1D.
getWindow() - Method in class com.imsl.chart3d.ColormapLegend
Returns the window for a ColormapLegend.
getX() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "X" attribute.
getX() - Method in class com.imsl.datamining.AssociationRule
The X components of the association rule.
getX() - Method in class com.imsl.stat.GARCH
Returns the estimated parameter array, x.
getXHi() - Method in class com.imsl.stat.EmpiricalQuantiles
Returns the smallest element of x greater than or equal to the desired quantile.
getXKnots() - Method in class com.imsl.math.Spline2D
Returns the knot sequences in the x-direction.
getXLo() - Method in class com.imsl.stat.EmpiricalQuantiles
Returns the largest element of x less than or equal to the desired quantile.
getXOrder() - Method in class com.imsl.math.Spline2DLeastSquares
Returns the order of the spline in the x-direction.
getXWeights() - Method in class com.imsl.math.Spline2DLeastSquares
Returns the weights for the least-squares fit in the x-direction.
getXY() - Method in class com.imsl.datamining.PredictiveModel
Returns a copy of the xy data.
getY() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Y" attribute.
getY() - Method in class com.imsl.datamining.AssociationRule
The Y components of the association rule.
getYearBasis() - Method in class com.imsl.finance.DayCountBasis
Returns the (days in year) portion of the Day Count Basis.
getYKnots() - Method in class com.imsl.math.Spline2D
Returns the knot sequences in the y-direction.
getYOrder() - Method in class com.imsl.math.Spline2DLeastSquares
Returns the order of the spline in the y-direction.
getYProb(int) - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns a class probability at the current node, if the response variable is of categorical type.
getYProbs() - Method in class com.imsl.datamining.decisionTree.TreeNode
Returns class probabilities at the current node, if the response variable is of categorical type.
getYWeights() - Method in class com.imsl.math.Spline2DLeastSquares
Returns the weights for the least-squares fit in the y-direction.
getZ() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Z" attribute.
getZ() - Method in class com.imsl.stat.KolmogorovOneSample
Returns the normalized D statistic without the continuity correction applied.
getZ() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns the normalized D statistic without the continuity correction applied.
GINI_INDEX - Static variable in class com.imsl.datamining.decisionTree.DecisionTreeInfoGain.GainCriteria
A measure of statistical dispersion.
gradient(double[], double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockGradObjective
 
gradient(double[], double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.GradObjective
 
gradient(double[], double[]) - Method in interface com.imsl.math.MinConGenLin.Gradient
Public interface for the user-supplied function to compute the gradient at point x.
gradient(double[], int, double[]) - Method in interface com.imsl.math.MinConNLP.Gradient
Computes the value of the gradient of the function at the given point.
gradient(double[], double[]) - Method in interface com.imsl.math.MinUnconMultiVar.Gradient
Public interface for the gradient of the multivariate function to be minimized.
gradient(double[]) - Method in class com.imsl.math.RadialBasis
Returns the gradient of the radial basis approximation at a point.
GradientBoosting - Class in com.imsl.datamining
Performs stochastic gradient boosting for a single response variable and multiple predictor variables.
GradientBoosting(double[][], int, PredictiveModel.VariableType[]) - Constructor for class com.imsl.datamining.GradientBoosting
Constructs a GradientBoosting object for a single response variable and multiple predictor variables.
GradientBoosting(PredictiveModel) - Constructor for class com.imsl.datamining.GradientBoosting
Constructs a gradient boosting object.
GradientBoosting.LossFunctionType - Class in com.imsl.datamining
The loss function type as specified by the error measure.
graphics - Variable in class com.imsl.chart.Draw
 
GREEN - Static variable in interface com.imsl.chart.Colormap
Linear green colormap.
GREEN_PINK - Static variable in interface com.imsl.chart.Colormap
Green/pink colormap.
GREEN_RED_BLUE_WHITE - Static variable in interface com.imsl.chart.Colormap
Green/red/blue/white colormap.
GREEN_WHITE_EXPONENTIAL - Static variable in interface com.imsl.chart.Colormap
Exponential green/white colormap.
GREEN_WHITE_LINEAR - Static variable in interface com.imsl.chart.Colormap
Linear green/white colormap.
Grid - Class in com.imsl.chart
Draws the grid lines perpendicular to an axis.
GRID_HEXAGONAL - Static variable in class com.imsl.datamining.KohonenSOM
Indicates a hexagonal grid.
GRID_RECTANGULAR - Static variable in class com.imsl.datamining.KohonenSOM
Indicates a rectangular grid.
GridPolar - Class in com.imsl.chart
Draws the grid lines for a polar plot.

H

hashCode() - Method in class com.imsl.math.Complex
Returns a hashcode for this Complex.
hasMoreTokens() - Method in class com.imsl.io.Tokenizer
Returns true if a call to nextToken will not generate an exception.
haveErrorBarProperties - Variable in class com.imsl.chart.Draw
 
haveFillProperties - Variable in class com.imsl.chart.Draw
 
haveImageProperties - Variable in class com.imsl.chart.Draw
 
haveLineProperties - Variable in class com.imsl.chart.Draw
 
haveMarkerProperties - Variable in class com.imsl.chart.Draw
 
haveTextProperties - Variable in class com.imsl.chart.Draw
 
Heatmap - Class in com.imsl.chart
Heatmap creates a chart from a two-dimensional array of double precision values or Color values.
Heatmap(AxisXY, double, double, double, double, Color[][]) - Constructor for class com.imsl.chart.Heatmap
Creates a Heatmap from an array of Color values.
Heatmap(AxisXY, double, double, double, double, double, double, double[][], Colormap) - Constructor for class com.imsl.chart.Heatmap
Creates a Heatmap from an array of double values and a Colormap.
Heatmap.Legend - Class in com.imsl.chart
A legend for use with a heatmap.
hessian(double[], double[][]) - Method in interface com.imsl.math.MinUnconMultiVar.Hessian
Public interface for the Hessian of the multivariate function to be minimized.
HiddenLayer - Class in com.imsl.datamining.neural
Hidden layer in a neural network.
HighLowClose - Class in com.imsl.chart
High-low-close plot of stock data.
HighLowClose(AxisXY, Date, double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose
Constructs a high-low-close chart node beginning with specified start date.
HighLowClose(AxisXY, Date, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose
Constructs a high-low-close-open chart node beginning with specified start date.
HighLowClose(AxisXY, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose
Constructs a high-low-close chart node at specified axis points.
HighLowClose(AxisXY, double[], double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose
Constructs a high-low-close-open chart node at specified axis points.
HoltWintersExponentialSmoothing - Class in com.imsl.stat
Calculates parameters and forecasts using the Holt-Winters Multiplicative or Additive forecasting method for seasonal data.
HoltWintersExponentialSmoothing(int, double[]) - Constructor for class com.imsl.stat.HoltWintersExponentialSmoothing
Constructor for HoltWintersExponentialSmoothing.
horizontalStripe(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a horizontally striped pattern.
HUBER_M - Static variable in class com.imsl.datamining.GradientBoosting.LossFunctionType
The loss criteria is the Huber-M weighted squared error and absolute deviation error with parameter alpha.
Hyperbolic - Class in com.imsl.math
Pure Java implementation of the hyperbolic functions and their inverses.
hypergeometric(int, int, int, int) - Static method in class com.imsl.stat.Cdf
Evaluates the hypergeometric cumulative probability distribution function.
hypergeometric(int, int, int, int) - Static method in class com.imsl.stat.Pdf
Evaluates the hypergeometric probability density function.
HyperRectangleQuadrature - Class in com.imsl.math
HyperRectangleQuadrature integrates a function over a hypercube.
HyperRectangleQuadrature(int) - Constructor for class com.imsl.math.HyperRectangleQuadrature
Constructs a HyperRectangleQuadrature object.
HyperRectangleQuadrature(RandomSequence) - Constructor for class com.imsl.math.HyperRectangleQuadrature
Constructs a HyperRectangleQuadrature object.
HyperRectangleQuadrature.Function - Interface in com.imsl.math
Public interface function for the HyperRectangleQuadrature class.

I

I(double, int) - Static method in class com.imsl.math.Bessel
Evaluates a sequence of modified Bessel functions of the first kind with integer order and real argument.
I(double, double, int) - Static method in class com.imsl.math.Bessel
Evaluates a sequence of modified Bessel functions of the first kind with real order and real argument.
i - Static variable in class com.imsl.math.Complex
The imaginary unit.
IEEE - Class in com.imsl.math
Pure Java implementation of the IEEE 754 functions as specified in IEEE Standard for Binary Floating-Point Arithmetic, ANSI/IEEE Standard 754-1985 (IEEE, New York).
IEEEremainder(double, double) - Static method in class com.imsl.math.JMath
Returns the IEEE remainder from x divided by p.
IGNORE - Static variable in class com.imsl.datamining.PredictiveModel.VariableType
The associated variable will be ignored.
ignoreMissingValues(boolean) - Method in class com.imsl.datamining.NaiveBayesClassifier
Specifies whether or not missing values will be ignored during the training process.
ilogb(double) - Static method in class com.imsl.math.IEEE
Return the binary exponent of non-zero x.
imag() - Method in class com.imsl.math.Complex
Returns the imaginary part of a Complex object.
imag(Complex) - Static method in class com.imsl.math.Complex
Returns the imaginary part of a Complex object.
IMAGE - Static variable in class com.imsl.chart.Draw
 
image(ImageIcon) - Static method in class com.imsl.chart.FillPaint
Returns a tiling of an image.
IMAGE_FACTOR_ANALYSIS - Static variable in class com.imsl.stat.FactorAnalysis
Indicates image factor analysis.
imageObserver - Variable in class com.imsl.chart.Draw
 
IMSLException - Exception in com.imsl
Signals that a mathematical exception has occurred.
IMSLException() - Constructor for exception com.imsl.IMSLException
Constructs an IMSLException with no detail message.
IMSLException(String) - Constructor for exception com.imsl.IMSLException
Constructs an IMSLException with the specified detail message.
IMSLException(String, String, Object[]) - Constructor for exception com.imsl.IMSLException
Constructs an IMSLException with the specified detail message.
IMSLFormatter - Class in com.imsl
Simple formatter for classes that implement logging.
IMSLFormatter() - Constructor for class com.imsl.IMSLFormatter
 
IMSLRuntimeException - Exception in com.imsl
Signals that an error has occurred.
IMSLRuntimeException() - Constructor for exception com.imsl.IMSLRuntimeException
Constructs an IMSLRuntimeException with no detail message.
IMSLRuntimeException(String) - Constructor for exception com.imsl.IMSLRuntimeException
Constructs an IMSLRuntimeException with the specified detail message.
IMSLRuntimeException(String, String, Object[]) - Constructor for exception com.imsl.IMSLRuntimeException
Constructs an IMSLRuntimeException with the specified detail message.
IMSLUnexpectedErrorException - Exception in com.imsl
Signals that an unexpected error has occurred.
IMSLUnexpectedErrorException() - Constructor for exception com.imsl.IMSLUnexpectedErrorException
Constructs an IMSLUnexpectedErrorException.
incrementEpochCount() - Method in class com.imsl.datamining.neural.EpochTrainer
Increments the epoch counter.
index - Variable in class com.imsl.math.ComplexSparseMatrix.SparseArray
Jagged array containing column indices.
index - Variable in class com.imsl.math.SparseMatrix.SparseArray
Jagged array containing column indices.
INFINITY_NORM - Static variable in class com.imsl.stat.ClusterKNN
Indicates the distance is computed using the L_{infty} norm method.
INFINITY_NORM - Static variable in class com.imsl.stat.Dissimilarities
Indicates the maximum difference (L_infty norm) distance method.
infinityNorm(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Return the infinity norm of a Complex matrix.
infinityNorm() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the infinity norm of the matrix.
infinityNorm(double[][]) - Static method in class com.imsl.math.Matrix
Return the infinity norm of a matrix.
infinityNorm() - Method in class com.imsl.math.SparseMatrix
Returns the infinity norm of the matrix.
information(int[], int[], double[], double[], boolean) - Method in class com.imsl.datamining.decisionTree.DecisionTreeInfoGain
Returns the expected information of a variable y over a partition determined by the variable x.
init() - Method in class com.imsl.chart.ChartServlet
 
init(double[], double[], double, double[], double[], double[], double[]) - Method in interface com.imsl.math.FeynmanKac.InitialData
Method that allows for adjustment of initial data or as an opportunity for output during the integration steps.
innerproduct(double[], double[]) - Method in interface com.imsl.math.GenMinRes.VectorProducts
Used to compute the inner product of 2 vectors for the Gram-Schmidt implementation.
INNOVATIONAL - Static variable in class com.imsl.stat.ARMAOutlierIdentification
Indicates detection of an innovational outlier.
INNOVATIONAL - Static variable in class com.imsl.stat.AutoARIMA
Indicates detection of an innovational outlier.
InputLayer - Class in com.imsl.datamining.neural
Input layer in a neural network.
InputNode - Class in com.imsl.datamining.neural
A Node in the InputLayer.
insertRow() - Method in class com.imsl.io.AbstractFlatFile
Inserts the contents of the insert row into this ResultSet object and into the database.
INTEGER_VARIABLE - Static variable in class com.imsl.io.MPSReader
Variable must be an integer.
integral(double, double) - Method in class com.imsl.math.BSpline
Returns the value of an integral of the B-spline.
integral(double, double) - Method in class com.imsl.math.Spline
Returns the value of an integral of the spline.
integral(double, double, double, double) - Method in class com.imsl.math.Spline2D
Returns the value of an integral of a tensor-product spline on a rectangular domain.
INTERSECTION - Static variable in class com.imsl.stat.TimeSeriesOperations.MergeRule
The merge operation includes time points and values only at the matching time points and applies the CombineMethod to the values at the matching time points.
intrate(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the interest rate of a fully invested security.
intValue() - Method in class com.imsl.math.Complex
Returns the value of the real part as an int.
intValue() - Method in class com.imsl.math.Physical
Returns the value of this dimensionless object.
InvCdf - Class in com.imsl.stat
Inverse cumulative probability distribution functions.
inverse() - Method in class com.imsl.math.Cholesky
Returns the inverse of this matrix
inverse() - Method in class com.imsl.math.ComplexLU
Returns the inverse of the matrix used to construct this instance.
inverse() - Method in class com.imsl.math.LU
Returns the inverse of the matrix used to construct this instance.
inverse() - Method in class com.imsl.math.SVD
Compute the Moore-Penrose generalized inverse of a real matrix.
InverseCdf - Class in com.imsl.stat
Inverse of user-supplied cumulative distribution function.
InverseCdf(CdfFunction) - Constructor for class com.imsl.stat.InverseCdf
Constructor for the inverse of a user-supplied cummulative distribution function.
InverseCdf.DidNotConvergeException - Exception in com.imsl.stat
The iteration did not converge
InverseCdf.DidNotConvergeException(String) - Constructor for exception com.imsl.stat.InverseCdf.DidNotConvergeException
Constructs a DidNotConvergeException object.
InverseCdf.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.stat.InverseCdf.DidNotConvergeException
Constructs a DidNotConvergeException object.
inverseLowerTriangular(double[][]) - Static method in class com.imsl.math.Matrix
Returns the inverse of the lower triangular matrix a.
inverseUpperTriangular(double[][]) - Static method in class com.imsl.math.Matrix
Returns the inverse of the upper triangular matrix a.
ipmt(double, int, int, double, double, int) - Static method in class com.imsl.finance.Finance
Returns the interest payment for an investment for a given period.
ipvt - Variable in class com.imsl.math.ComplexLU
Vector of length n containing the pivot sequence for the factorization.
ipvt - Variable in class com.imsl.math.LU
Vector of length n containing the pivot sequence for the factorization.
irr(double[]) - Static method in class com.imsl.finance.Finance
Returns the internal rate of return for a schedule of cash flows.
irr(double[], double) - Static method in class com.imsl.finance.Finance
Returns the internal rate of return for a schedule of cash flows.
isA0Flag() - Method in class com.imsl.stat.VectorAutoregression
Returns the state of A0Flag.
isAfterLast() - Method in class com.imsl.io.AbstractFlatFile
Indicates whether the cursor is after the last row in this ResultSet object.
isAncestorOf(AbstractChartNode) - Method in class com.imsl.chart.AbstractChartNode
Returns true if this node is an ancestor of the argument node.
isAttributeSet(String) - Method in class com.imsl.chart.AbstractChartNode
Determines if an attribute is defined (may have been inherited).
isAttributeSetAtThisNode(String) - Method in class com.imsl.chart.AbstractChartNode
Determines if an attribute is defined in this node (not inherited).
isAutoPruningFlag() - Method in class com.imsl.datamining.decisionTree.DecisionTree
Returns the auto-pruning flag.
isBeforeFirst() - Method in class com.imsl.io.AbstractFlatFile
Indicates whether the cursor is before the first row in this ResultSet object.
isBitSet(int, int) - Static method in class com.imsl.chart.AbstractChartNode
Returns true if the bit set in flag is set in mask.
isBitSet(int, int) - Static method in class com.imsl.chart.ChartNode
Returns true if the bit set in flag is set in mask.
isClosed() - Method in class com.imsl.io.FlatFile
Retrieves whether this ResultSet object has been closed.
isDateIncrementInMillis() - Method in class com.imsl.stat.TimeSeries
Returns a boolean indicating whether or not the TimeSeries object has a date increment expressed in milliseconds.
isFirst() - Method in class com.imsl.io.AbstractFlatFile
Indicates whether the cursor is on the first row of this ResultSet object.
isHasDates() - Method in class com.imsl.stat.TimeSeries
Returns a boolean indicating whether or not the TimeSeries has a non-null dates attribute.
isInvertible(double[]) - Method in class com.imsl.stat.ARMAMaxLikelihood
Tests whether the coefficients in ma are invertible
isLast() - Method in class com.imsl.io.AbstractFlatFile
Indicates whether the cursor is on the last row of this ResultSet object.
isMustFitModelFlag() - Method in class com.imsl.datamining.PredictiveModel
Returns the current value of the mustFitModel flag.
isNaN(double) - Static method in class com.imsl.math.IEEE
NaN test on an argument of type double.
isNoMoreProgress() - Method in class com.imsl.math.QuadraticProgramming
Returns true if due to computer rounding error, a change in the variables fail to improve the objective function.
isProportionalWidth() - Method in class com.imsl.chart.BoxPlot
Returns the value of the attribute "ProportionalWidth".
isStationary(double[]) - Method in class com.imsl.stat.ARMAMaxLikelihood
Tests whether the coefficients in ar are stationary.
isTerminalNode(int) - Method in class com.imsl.datamining.decisionTree.Tree
Returns the terminal node indicator of the node at the given index.
isUserFixedNClasses() - Method in class com.imsl.datamining.PredictiveModel
Returns true if the number of classes was fixed by the user.
isWeekday(GregorianCalendar) - Method in class com.imsl.chart.TransformDate
Returns true if the specified date is a weekday.
isWrapAround() - Method in class com.imsl.datamining.KohonenSOM
Returns whether the opposite edges are connected or not.
isWrapperFor(Class) - Method in class com.imsl.io.FlatFile
Returns true if this either implements the interface argument or is directly or indirectly a wrapper for an object that does.
Itemsets - Class in com.imsl.datamining
Object containing a set of frequent items and the number of transactions examined to obtain the frequent item set.
iterator() - Method in class com.imsl.io.MPSReader.Row
Returns an iterator over the elements in this row.

J

J(double, int) - Static method in class com.imsl.math.Bessel
Evaluates a sequence of Bessel functions of the first kind with integer order and real argument.
J(double, double, int) - Static method in class com.imsl.math.Bessel
Evaluate a sequence of Bessel functions of the first kind with real order and real positive argument.
jacobian(double[], double[][]) - Method in interface com.imsl.math.NonlinLeastSquares.Jacobian
Public interface for the nonlinear least squares function.
jacobian(double[]) - Method in interface com.imsl.math.NumericalDerivatives.Jacobian
User-supplied function to compute the Jacobian.
jacobian(double, double[], double[]) - Method in interface com.imsl.math.OdeAdamsGear.Jacobian
Used to compute the Jacobian of the function at t.
jacobian(double[], double[][]) - Method in interface com.imsl.math.ZeroSystem.Jacobian
Returns the value of the Jacobian at the given point.
JFrameChart - Class in com.imsl.chart
JFrameChart is a JFrame that contains a chart.
JFrameChart() - Constructor for class com.imsl.chart.JFrameChart
Creates new JFrameChart to display a chart.
JFrameChart(Chart) - Constructor for class com.imsl.chart.JFrameChart
Creates new JFrameChart to display a given chart.
JFrameChart3D - Class in com.imsl.chart3d
JFrameChart3D is a JFrame that contains a chart.
JFrameChart3D() - Constructor for class com.imsl.chart3d.JFrameChart3D
Creates new JFrameChart3D to display a chart.
JFrameChart3D(Chart3D) - Constructor for class com.imsl.chart3d.JFrameChart3D
Creates new JFrameChart3D to display a given chart.
JMath - Class in com.imsl.math
Pure Java implementation of the standard java.lang.Math class.
JPanelChart - Class in com.imsl.chart
A Swing JPanel that contains a chart.
JPanelChart() - Constructor for class com.imsl.chart.JPanelChart
Creates new JPanelChart.
JPanelChart(Chart) - Constructor for class com.imsl.chart.JPanelChart
Creates new JPanelChart using a given Chart object.
JspBean - Class in com.imsl.chart
JspBean is used to refer to charts in a Java Server Page that are later rendered using the ChartServlet.
JspBean() - Constructor for class com.imsl.chart.JspBean
Creates a JspBean object.

K

K(double, int) - Static method in class com.imsl.math.Bessel
Evaluates a sequence of modified Bessel functions of the third kind with integer order and real argument.
K(double, double, int) - Static method in class com.imsl.math.Bessel
Evaluates a sequence of modified Bessel functions of the third kind with fractional order and real argument.
KalmanFilter - Class in com.imsl.stat
Performs Kalman filtering and evaluates the likelihood function for the state-space model.
KalmanFilter(double[], double[][], int, double, double) - Constructor for class com.imsl.stat.KalmanFilter
Constructor for KalmanFilter.
KaplanMeierECDF - Class in com.imsl.stat
Computes the Kaplan-Meier reliability function estimates or the CDF based on failure data that may be multi-censored.
KaplanMeierECDF(double[]) - Constructor for class com.imsl.stat.KaplanMeierECDF
Constructor for KaplanMeierECDF.
KaplanMeierEstimates - Class in com.imsl.stat
Computes Kaplan-Meier (or product-limit) estimates of survival probabilities for a sample of failure times that possibly contain right consoring.
KaplanMeierEstimates(double[][]) - Constructor for class com.imsl.stat.KaplanMeierEstimates
Constructor for KaplanMeierEstimates.
kappa(double, double) - Method in interface com.imsl.math.FeynmanKac.PdeCoefficients
Returns the value of the kappa coefficient at the given point.
keySet() - Method in class com.imsl.chart.xml.ChartXML
Returns the Set view of all id's defined in the XML file.
knot - Variable in class com.imsl.math.BSpline
The knot array of length n + order, where n is the number of coefficients in the B-spline.
KohonenSOM - Class in com.imsl.datamining
A Kohonen self organizing map.
KohonenSOM(int, int, int) - Constructor for class com.imsl.datamining.KohonenSOM
Constructor for a KohonenSOM object.
KohonenSOMTrainer - Class in com.imsl.datamining
Trains a Kohonen network.
KohonenSOMTrainer() - Constructor for class com.imsl.datamining.KohonenSOMTrainer
 
KolmogorovOneSample - Class in com.imsl.stat
The class KolmogorovOneSample performs a Kolmogorov-Smirnov goodness-of-fit test in one sample.
KolmogorovOneSample(CdfFunction, double[]) - Constructor for class com.imsl.stat.KolmogorovOneSample
Constructs a one sample Kolmogorov-Smirnov goodness-of-fit test.
KolmogorovTwoSample - Class in com.imsl.stat
Performs a Kolmogorov-Smirnov two-sample test.
KolmogorovTwoSample(double[], double[]) - Constructor for class com.imsl.stat.KolmogorovTwoSample
Constructs a two sample Kolmogorov-Smirnov goodness-of-fit test.
kurtosis(double[]) - Static method in class com.imsl.stat.Summary
Returns the kurtosis of the given data set.
kurtosis(double[], double[]) - Static method in class com.imsl.stat.Summary
Returns the kurtosis of the given data set and associated weights.

L

L1_NORM - Static variable in class com.imsl.stat.ClusterKNN
Indicates the distance is computed using the L_1 norm method.
L1_NORM - Static variable in class com.imsl.stat.Dissimilarities
Indicates the sum of the absolute differences (L_1 norm) distance method.
L2_NORM - Static variable in class com.imsl.stat.ClusterKNN
Indicates the distance is computed using the L_2 norm, or Euclidean distance measurement.
L2_NORM - Static variable in class com.imsl.stat.Dissimilarities
Indicates the Euclidean distance method (L_2 norm).
LABEL_TYPE_NONE - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate the an element is not to be labeled.
LABEL_TYPE_PERCENT - Static variable in class com.imsl.chart.ChartNode
Flag used to indicate that a pie slice is to be labeled with a percentage value.
LABEL_TYPE_TITLE - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that an element is to be labeled with the value of its title attribute.
LABEL_TYPE_X - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that an element is to be labeled with the value of its x-coordinate.
LABEL_TYPE_Y - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that an element is to be labeled with the value of its y-coordinate.
LABEL_TYPE_Z - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that an element is to be labeled with the value of its y-coordinate.
LackOfFit - Class in com.imsl.stat
Performs lack-of-fit test for a univariate time series or transfer function given the appropriate correlation function.
LAST - Static variable in class com.imsl.chart.Draw
Flag for the last data marker.
last() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the last row in this ResultSet object.
Layer - Class in com.imsl.datamining.neural
The base class for Layers in a neural network.
Layer(FeedForwardNetwork) - Constructor for class com.imsl.datamining.neural.Layer
Constructs a Layer.
LEAST_ABSOLUTE_DEVIATION - Static variable in class com.imsl.datamining.GradientBoosting.LossFunctionType
The loss criteria is least absolute deviation error.
LEAST_SQUARES - Static variable in class com.imsl.datamining.GradientBoosting.LossFunctionType
The loss criteria is least squared error.
LEAST_SQUARES - Static variable in class com.imsl.stat.ARAutoUnivariate
Indicates that least-squares should be used for estimating the coefficients in the time series.
LEAST_SQUARES - Static variable in class com.imsl.stat.ARMA
Indicates autoregressive and moving average parameters are estimated by a least-squares procedure.
LEAST_SQUARES - Static variable in class com.imsl.stat.ARMAEstimateMissing
Estimate autoregressive coefficients using least squares.
LeastSquaresTrainer - Class in com.imsl.datamining.neural
Trains a FeedForwardNetwork using a Levenberg-Marquardt algorithm for minimizing a sum of squares error.
LeastSquaresTrainer() - Constructor for class com.imsl.datamining.neural.LeastSquaresTrainer
Creates a LeastSquaresTrainer.
LEAVE_OUT_LAST - Static variable in class com.imsl.stat.RegressorsForGLM
The dummies are the first n-1 indicator variables.
LEAVE_OUT_ONE - Static variable in class com.imsl.stat.DiscriminantAnalysis
Indicates leave-out-one classification method.
leftBoundaries(double, double[][]) - Method in interface com.imsl.math.FeynmanKac.Boundaries
Returns the coefficient values of the left boundary conditions.
Legend - Class in com.imsl.chart
The chart legend.
Legend(Chart) - Constructor for class com.imsl.chart.Legend
 
LENGTH - Static variable in class com.imsl.math.Physical
 
LEVEL_SHIFT - Static variable in class com.imsl.stat.ARMAOutlierIdentification
Indicates detection of a level shift outlier.
LEVEL_SHIFT - Static variable in class com.imsl.stat.AutoARIMA
Indicates detection of a level shift outlier.
LicenseManagerException - Exception in com.imsl
A LicenseManagerException exception is thrown if a license to use the product cannot be obtained.
LifeTables - Class in com.imsl.stat
Computes population (current) or cohort life tables based upon the observed population sizes at the middle (for population table) or the beginning (for cohort table) of some user specified age intervals.
LifeTables(int[], double[], double[]) - Constructor for class com.imsl.stat.LifeTables
Constructs a new LifeTables instance.
LillieforsTest() - Method in class com.imsl.stat.NormalityTest
Performs the Lilliefors test.
LINE - Static variable in class com.imsl.chart.Draw
 
LINEAR - Static variable in interface com.imsl.datamining.neural.Activation
The identity activation function, g(x) = x.
LINEAR - Static variable in class com.imsl.stat.DiscriminantAnalysis
Indicates a linear discrimination method.
LINEAR_AT_RESTART_AND_TERMINATION - Static variable in class com.imsl.math.GenMinRes
Indicates residual updating is to be done by linear combination upon restarting and at termination.
LINEAR_AT_RESTART_ONLY - Static variable in class com.imsl.math.GenMinRes
Indicates residual updating is to be done by linear combination upon restarting only.
LinearRegression - Class in com.imsl.stat
Fits a multiple linear regression model with or without an intercept.
LinearRegression(int, boolean) - Constructor for class com.imsl.stat.LinearRegression
Constructs a new linear regression object.
LinearRegression.CaseStatistics - Class in com.imsl.stat
Inner Class CaseStatistics allows for the computation of predicted values, confidence intervals, and diagnostics for detecting outliers and cases that greatly influence the fitted regression.
LinearRegression.CoefficientTTests - Class in com.imsl.stat
Contains statistics related to the regression coefficients.
lineColor - Variable in class com.imsl.chart.Draw
 
lineDashPattern - Variable in class com.imsl.chart.Draw
 
lineWidth - Variable in class com.imsl.chart.Draw
 
link(Node, Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Establishes a Link between two Nodes.
link(Node, Node, double) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Establishes a Link between two Nodes with a specified weight.
Link - Class in com.imsl.datamining.neural
A link in a neural network.
LINKAGE_AVG_BETWEEN_CLUSTERS - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates the average distance between (average distance between objects in the two clusters) method.
LINKAGE_AVG_WITHIN_CLUSTERS - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates the average distance within (average distance between objects within the merged cluster) method.
LINKAGE_COMPLETE - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates the complete linkage (maximum distance) method.
LINKAGE_SINGLE - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates the single linkage (minimum distance) method.
LINKAGE_WARDS - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates the Ward's method.
linkAll(Layer, Layer) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Link all of the Nodes in one Layer to all of the Nodes in another Layer.
linkAll() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
For each Layer in the Network, link each Node in the Layer to each Node in the next Layer.
log(Complex) - Static method in class com.imsl.math.Complex
Returns the logarithm of a Complex z, with a branch cut along the negative real axis.
log(double) - Static method in class com.imsl.math.JMath
Returns the natural logarithm of a double.
log10(double) - Static method in class com.imsl.math.Sfun
Returns the common (base 10) logarithm of a double.
log1p(double) - Static method in class com.imsl.math.Hyperbolic
Returns log(1+x), the logarithm of (x plus 1).
logBeta(double, double) - Static method in class com.imsl.math.Sfun
Returns the logarithm of the beta function.
logGamma(double) - Static method in class com.imsl.math.Sfun
Returns the logarithm of the absolute value of the Gamma function.
LOGISTIC - Static variable in interface com.imsl.datamining.neural.Activation
The logistic activation function, g(x)=frac{1}{1+e^{-x}}.
logistic(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the logistic cumulative probability distribution function.
logistic(double, double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the logistic cumulative probability distribution function.
logistic(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the logistic probability density function.
LOGISTIC_TABLE - Static variable in interface com.imsl.datamining.neural.Activation
The logistic activation function computed using a table.
logNormal(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the standard lognormal cumulative probability distribution function.
logNormal(double, double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the standard lognormal cumulative probability distribution function.
logNormal(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the standard lognormal probability density function.
LogNormalDistribution - Class in com.imsl.stat
Evaluates a lognormal probability density for a given set of data.
LogNormalDistribution() - Constructor for class com.imsl.stat.LogNormalDistribution
 
longValue() - Method in class com.imsl.math.Complex
Returns the value of the real part as a long.
longValue() - Method in class com.imsl.math.Physical
Returns the value of this dimensionless object.
LOWER_TRIANGULAR - Static variable in class com.imsl.math.PrintMatrix
This flag as the argument to setMatrixType, indicates that only the lower triangular elements of the matrix are to be printed.
LU - Class in com.imsl.math
LU factorization of a matrix of type double.
LU(double[][]) - Constructor for class com.imsl.math.LU
Creates the LU factorization of a square matrix of type double.

M

MAHALANOBIS - Static variable in class com.imsl.stat.Dissimilarities
Indicates the Mahalanobis distance method.
main(String[]) - Static method in class com.imsl.chart.xml.ChartXML
Displays a chart created from an XML file.
main(String[]) - Static method in class com.imsl.Version
Print the version information about the environment and this library.