Class 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 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