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ARAutoUnivariateAIC Property
The final estimate for Akaike's Information Criterion (AIC) at the optimum.

Namespace: Imsl.Stat
Assembly: ImslCS (in ImslCS.dll) Version: 6.5.2.0
Syntax
public double AIC { get; }

Property Value

Type: Double
A double scalar value which is an approximation to \mbox{AIC} = -2\ln(L)+2p, where L is the value of the maximum likelihood function evaluated at the parameter estimates. The approximation uses the calculation
\mbox{AIC} \approx (\rm{n-maxlag})\ln({\hat {\sigma}}^2)+2(p+1)+(\rm{n-maxlag})(\ln(2\pi)+1),
where {\hat {\sigma}}^2 is an estimate of the residual variance of the series, commonly known in time series analysis as the innovation variance, and n is the number of observations in the time series z(n=z.Length).
Exceptions
ExceptionCondition
MatrixSingularException is thrown if the input matrix is singular.
TooManyCallsException is thrown if the number of calls to the function has exceeded the maximum number of iterations times the number of moving average (MA) parameters + 1.
IncreaseErrRelException is thrown if the bound for the relative error is too small.
NewInitialGuessException is thrown if the iteration has not made good progress.
IllConditionedException is thrown if the problem is ill-conditioned.
TooManyIterationsException is thrown if the maximum number of iterations is exceeded.
TooManyFunctionEvaluationsException is thrown if the maximum number of function evaluations is exceeded.
TooManyJacobianEvalException is thrown if the maximum number of Jacobian evaluations is exceeded.
SingularTriangularMatrixException is thrown if the input triangular matrix is singular.
NonStationaryException is thrown if the final maximum likelihood estimates for the time series are nonstationary.
See Also