The ARMAMaxLikelihood type exposes the following members.
Constructors
Name | Description | |
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ARMAMaxLikelihood |
Constructor for ARMAMaxLikelihood.
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Methods
Name | Description | |
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Compute |
Computes the exact maximum likelihood estimates for the autoregressive
and moving average parameters of an ARMA time series.
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Equals | (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 |
Returns forecasts for lead times
at origins
z.Length-BackwardOrigin-1+j where
.
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GetAR |
Returns the final autoregressive parameter estimates.
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GetDeviations |
Returns the deviations for each forecast used for calculating the
forecast confidence limits.
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GetForecast |
Returns forecasts
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GetGradients |
Returns the gradients for the final parameter estimates.
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GetHashCode |
Serves as a hash function for a particular type.
(Inherited from Object.) | |
GetMA |
Returns the final moving average parameter estimates.
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GetPsiWeights |
Returns the psi weights used for calculating forecasts from the infinite
order moving average form of the ARMA model.
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GetResiduals |
The current values of the vector of residuals.
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GetTimeSeries |
Returns the time series used to construct ARMAMaxLikelihood.
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GetType |
Gets the Type of the current instance.
(Inherited from Object.) | |
IsInvertible |
Tests whether the coefficients in ma are invertible.
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IsStationary |
Tests whether the coefficients in ar are stationary.
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MemberwiseClone |
Creates a shallow copy of the current Object.
(Inherited from Object.) | |
SetAR |
Sets the initial values for the autoregressive terms to the p
values in ar.
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SetMA |
Sets the initial values for the moving average terms to the q
values in ma.
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ToString | (Inherited from Object.) |
Properties
Name | Description | |
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BackwardOrigin |
The maximum backward origin.
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Confidence |
The confidence level for calculating confidence
limit deviations returned from GetDeviations.
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Constant |
The constant parameter in the ARMA series.
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GradientTolerance |
The gradient tolerance for the convergence algorithm.
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InnovationVariance |
The estimated innovation variance of this series.
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Likelihood |
The final estimate for , where
is equal to the likelihood function evaluated using the
final parameter estimates.
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MaxIterations |
The maximum number of iterations.
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Mean |
The mean used for centering the series.
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P |
The number of autoregressive terms in the ARMA model
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Q |
The number of moving average terms in the ARMA model
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Tolerance |
The tolerance for the convergence algorithm.
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