ARAutoUnivariate Members

ARAutoUnivariate Constructor ARAutoUnivariate constructor.

AIC	The final estimate for Akaike's Information Criterion (AIC) at the optimum.
BackwardOrigin	The maximum backward origin used in calculating the forecasts.
Confidence	The confidence level for calculating confidence limit deviations returned from `GetDeviations`.
Constant	The estimate for the constant parameter in the ARMA series.
ConvergenceTolerance	The tolerance level used to determine convergence of the nonlinear least-squares and maximum likelihood algorithms.
EstimationMethod	The estimation method used for estimating the final estimates for the autoregressive coefficients.
InnovationVariance	The final estimate for the innovation variance.
Likelihood	The final estimate for $L \approx e^{-(\mbox{AIC} - 2p)/2}$ , where p is the AR order, AIC is the value of Akaike's Information Criterion, and L is the likelihood function evaluated for the optimum autoregressive model.
MaxIterations	The maximum number of iterations used for estimating the autoregressive coefficients.
Maxlag	The current value used to represent the maximum number of autoregressive lags to achieve the minimum AIC.
Mean	The mean used to center the time series `z`.
Order	The order of the AR model selected with the minimum AIC.
TimsacConstant	The estimate for the constant parameter in the ARMA series.
TimsacVariance	The final estimate for the innovation variance calculated by the TIMSAC automatic AR modeling routine (UNIMAR).

Compute	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 `EstimationMethod`.
Equals (inherited from Object)	Determines whether the specified Object is equal to the current Object.
Forecast	Returns forecasts and associated confidence interval offsets.
GetAR	Returns the final autoregressive parameter estimates at the optimum AIC using the estimation method specified in `EstimationMethod`.
GetDeviations	Returns the deviations for each forecast used for calculating the forecast confidence limits.
GetForecast	Returns a specified number of forecasts beyond the last value in the series.
GetHashCode (inherited from Object)	Serves as a hash function for a particular type, suitable for use in hashing algorithms and data structures like a hash table.
GetResiduals	Returns the current values of the vector of residuals.
GetTimeSeries	Returns the time series used for estimating the minimum AIC and the autoregressive coefficients.
GetTimsacAR	Returns the final auto regressive parameter estimates at the optimum AIC estimated by the original TIMSAC routine (UNIMAR).
GetType (inherited from Object)	Gets the Type of the current instance.
ToString (inherited from Object)	Returns a String that represents the current Object.

Finalize (inherited from Object)	Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection.
MemberwiseClone (inherited from Object)	Creates a shallow copy of the current Object.