org.codehaus.jet.regression.estimators
Class SchwarzInformationCriterionEstimator
java.lang.Object
org.codehaus.jet.regression.estimators.AbstractInformationCriterionEstimator
org.codehaus.jet.regression.estimators.SchwarzInformationCriterionEstimator
- All Implemented Interfaces:
- InformationCriterionEstimator
public class SchwarzInformationCriterionEstimator
- extends AbstractInformationCriterionEstimator
Estimator for the Schwarz Information Criterion (SIC)
SIC(p)= log(sigma^2(p)+[p*log(T)]/T
- Author:
- Mauro Talevi
- See Also:
InformationCriterionEstimator
Method Summary |
protected double |
calculateIC(int p,
int T,
double var)
Calculate SIC |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
SchwarzInformationCriterionEstimator
public SchwarzInformationCriterionEstimator()
- Creates an SchwarzInformationCriterionEstimator with default regression estimator
SchwarzInformationCriterionEstimator
public SchwarzInformationCriterionEstimator(MultipleLinearRegressionEstimator regression)
- Creates an SchwarzInformationCriterionEstimator with given regression estimator
- Parameters:
regression
- the MultipleLinearRegressionEstimator
calculateIC
protected double calculateIC(int p,
int T,
double var)
- Calculate SIC
SIC(p)= log(sigma^2(p)+[p*log(T)]/T
- Specified by:
calculateIC
in class AbstractInformationCriterionEstimator
- Parameters:
p
- the lag orderT
- the sample sizevar
- the sample variance
- Returns:
- The SIC value
Copyright © 2006-2007. All Rights Reserved.