ARAutoUnivariate.Likelihood Property

ARAutoUnivariateLikelihood 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.

Namespace: Imsl.Stat
Assembly: ImslCS (in ImslCS.dll) Version: 6.5.2.0

Syntax

C++

Copy

public double Likelihood { get; }

Public ReadOnly Property Likelihood As Double
	Get

public:
property double Likelihood {
	double get ();
}

member Likelihood : float with get

Property Value

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

Exceptions

Exception	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.

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.

Reference

ARAutoUnivariate Class

Imsl.Stat Namespace