# SuanShu, a Java numerical and statistical library

com.numericalmethod.suanshu.model.daspremont2008

## Class CovarianceEstimation

• java.lang.Object
• com.numericalmethod.suanshu.model.daspremont2008.CovarianceEstimation

• public class CovarianceEstimation
extends Object
Estimates the covariance matrix by maximum likelihood. The maximum likelihood problem is $\max_{X} \log(\det X) - Tr(\Sigma X)-\rho Card(X)$
See Also:
• "A. d'Aspremont, "eq. 13," Identifying Small Mean Reverting Portfolios, 2008."
• "O. Banerjee, L. E. Ghaoui and A. d'Aspremont, "Model Selection Through Sparse Maximum Likelihood Estimation for multivariate Gaussian or Binary Data," Journal of Machine Learning Research, 9, pp. 485-516, March 2008."
• ### Constructor Summary

Constructors
Constructor and Description
CovarianceEstimation(Matrix Sigma, double rho)
Solves the maximum likelihood problem for covariance selection.
• ### Method Summary

All Methods
Modifier and Type Method and Description
SymmetricMatrix covariance()
SymmetricMatrix inverseCovariance()
• ### Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
• ### Constructor Detail

• #### CovarianceEstimation

public CovarianceEstimation(Matrix Sigma,
double rho)
Solves the maximum likelihood problem for covariance selection.
Parameters:
Sigma - the sample covariance matrix
rho - the penalty parameter
• ### Method Detail

• #### covariance

public SymmetricMatrix covariance()
• #### inverseCovariance

public SymmetricMatrix inverseCovariance()
Returns:
The solution to eq. 13

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