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arXiv · 0908.0143

A Pathwise Algorithm for Covariance Selection

Vijay Krishnamurthy·Alexandre d'Aspremont
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Abstract

Covariance selection seeks to estimate a covariance matrix by maximum likelihood while restricting the number of nonzero inverse covariance matrix coefficients. A single penalty parameter usually controls the tradeoff between log likelihood and sparsity in the inverse matrix. We describe an efficient algorithm for computing a full regularization path of solutions to this problem.

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Vijay Krishnamurthy, Alexandre d'Aspremont. 2009-08-02. A Pathwise Algorithm for Covariance Selection. https://arxiv.org/abs/0908.0143

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