org.codehaus.jet.regression.estimators
Class AkaikeInformationCriterionEstimator
java.lang.Object
org.codehaus.jet.regression.estimators.AbstractInformationCriterionEstimator
org.codehaus.jet.regression.estimators.AkaikeInformationCriterionEstimator
- All Implemented Interfaces:
- InformationCriterionEstimator
public class AkaikeInformationCriterionEstimator
- extends AbstractInformationCriterionEstimator
Estimator for the Akaike Information Criterion (AIC)
AIC(p)= -2T[ln(sigma^2(p)]+2p
- Author:
- Mauro Talevi
- See Also:
InformationCriterionEstimator
Method Summary |
protected double |
calculateIC(int p,
int T,
double var)
Calculate AIC |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
AkaikeInformationCriterionEstimator
public AkaikeInformationCriterionEstimator()
- Creates an AkaikeInformationCriterionEstimator with default regression estimator
AkaikeInformationCriterionEstimator
public AkaikeInformationCriterionEstimator(MultipleLinearRegressionEstimator regression)
- Creates an AkaikeInformationCriterionEstimator with given regression estimator
- Parameters:
regression
- the GeneralLinearRegression
calculateIC
protected double calculateIC(int p,
int T,
double var)
- Calculate AIC
AIC(p)= -2T[ln(sigma^2(p)]+2p
- Specified by:
calculateIC
in class AbstractInformationCriterionEstimator
- Parameters:
p
- the lag orderT
- the sample sizevar
- the sample variance
- Returns:
- The AIC value
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