ARAutoUnivariate Properties |
The ARAutoUnivariate type exposes the following members.
Name | Description | |
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AIC |
The final estimate for Akaike's Information Criterion (AIC)
at the optimum.
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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.
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InnovationVariance |
The final estimate for the innovation variance.
| |
Likelihood |
The final estimate for ,
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.
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Mean |
The mean used to center the time series z.
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NumberOfProcessors |
Perform the parallel calculations with the maximum possible number of
processors set to NumberOfProcessors.
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Order |
The order of the AR model selected with the minimum AIC.
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TimsacConstant |
The estimate for the constant parameter in the ARMA series.
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TimsacVariance |
The final estimate for the innovation variance calculated
by the TIMSAC automatic AR modeling routine (UNIMAR).
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