IMSL C# Numerical Library

ARAutoUnivariate.Likelihood Property

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.

public double Likelihood {get;}

Property Value

A double scalar equal to the estimate for the L \approx  e^{-(\mbox{AIC} - 2p)/2}.

Remarks

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.

Exceptions

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.

See Also

ARAutoUnivariate Class | Imsl.Stat Namespace