The ARMAOutlierIdentification type exposes the following members.

Constructors

NameDescription
ARMAOutlierIdentification
Constructor for ARMAOutlierIdentification.

Methods

NameDescription
Compute
Detects and determines outliers and simultaneously estimates the model parameters for the given time series.
ComputeForecasts
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.
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.)
GetAR
Returns the final autoregressive parameter 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.
GetOmegaWeights
Returns the \omega weights for the detected outliers.
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.
GetResidual
Returns the residuals.
GetTauStatistics
Returns the t value for each detected outlier.
GetType
Gets the Type of the current instance.
(Inherited from Object.)
MemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
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
Returns Akaike's information criterion (AIC).
AICC
Returns Akaike's Corrected Information Criterion (AICC).
BIC
Returns the Bayesian Information Criterion (BIC).
Confidence
The confidence level for calculating confidence limit deviations via method GetDeviations.
Constant
Returns the constant parameter estimate.
CriticalValue
The critical value used as a threshold during outlier detection.
Delta
The dampening effect parameter.
NumberOfOutliers
Returns the number of outliers detected.
RelativeError
The stopping criterion for use in the nonlinear equation solver.
ResidualStandardError
Returns the residual standard error of the outlier free series.

See Also