The AutoARIMA type exposes the following members.

Constructors

NameDescription
AutoARIMA
Constructor for AutoARIMA.

Methods

NameDescription
ComputeOverloaded.
Equals
Determines whether the specified Object is equal to the current Object.
(Inherited from Object.)
Finalize
Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection.
(Inherited from Object.)
Forecast
Computes forecasts, associated probability limits and \psi weights for the given outlier contaminated time series.
GetAR
Returns the final autoregressive parameter estimates of the optimum model.
GetCompleteTimes
Returns all time points at which the original series was observed, including values for times with missing values in x.
GetCompleteTimeSeries
Returns the original series with potentially missing values replaced by estimates.
GetDeviations
Returns the deviations used for calculating the forecast confidence limits.
GetForecast
Returns forecasts for the original outlier contaminated series.
GetHashCode
Serves as a hash function for a particular type.
(Inherited from Object.)
GetMA
Returns the final moving average parameter estimates of the optimum model.
GetOptimumModelOrder
Returns the order (p,0,q)\times(0,d,0)_s of the optimum model.
GetOutlierFreeForecast
Returns forecasts for the outlier free series.
GetOutlierFreeSeries
Returns the outlier free series.
GetOutlierStatistics
Returns the outlier statistics.
GetPsiWeights
Returns the \psi weights of the infinite order moving average form of the model.
GetResiduals
Returns the residuals.
GetType
Gets the Type of the current instance.
(Inherited from Object.)
MemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
SetDifferenceOrders
Defines the orders of the periodic differences used in the determination of the optimum model.
SetPeriods
Defines the periods used in the determination of the optimum model.
ToString
Returns a String that represents the current Object.
(Inherited from Object.)

Fields

NameDescription
ADDITIVE
Indicates detection of an additive outlier.
INNOVATIONAL
Indicates detection of an innovational outlier.
LEVEL_SHIFT
Indicates detection of a level shift outlier.
TEMPORARY_CHANGE
Indicates detection of a temporary change outlier.
UNABLE_TO_IDENTIFY
Indicates detection of an outlier that cannnot be categorized.

Properties

NameDescription
AccuracyTolerance
The tolerance value controlling the accuracy of the parameter estimates.
AIC
Akaike's information criterion (AIC) for the optimum model.
AICC
Akaike's Corrected Information Criterion (AICC) for the optimum model.
BIC
The Bayesian Information Criterion (BIC) for the optimum model.
Confidence
The confidence level used in the calculation of confidence limit deviations via method GetDeviations.
Constant
The constant parameter estimate for the optimum model.
CriticalValue
The critical value used as a threshold during outlier detection.
Delta
The dampening effect parameter.
MaximumARLag
The maximum AR lag used in the determination of the optimum (s,d) combination of method Compute(int[] arOrders, int[] maOrders).
ModelSelectionCriterion
The model selection criterion used in the optimum model search.
NumberOfOutliers
The number of detected outliers.
RelativeError
The stopping criterion for use in the nonlinear equation solver.
ResidualStandardError
The residual standard error of the outlier free series.

See Also