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.
A double
scalar equal to the estimate for the .
If MaximumLikelihood
is chosen as the EstimationMethod
, the exact likelihood evaluated for the optimum autoregressive model will be returned instead. Otherwise it is calculated using the approximation to the AIC.
Exception Type | Condition |
---|---|
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. |
ARAutoUnivariate Class | Imsl.Stat Namespace