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arXiv · 1512.05153

An algorithm for the multivariate group lasso with covariance estimation

Ines Wilms·Christophe Croux
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Abstract

We study a group lasso estimator for the multivariate linear regression model that accounts for correlated error terms. A block coordinate descent algorithm is used to compute this estimator. We perform a simulation study with categorical data and multivariate time series data, typical settings with a natural grouping among the predictor variables. Our simulation studies show the good performance of the proposed group lasso estimator compared to alternative estimators. We illustrate the method on a time series data set of gene expressions.

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Ines Wilms, Christophe Croux. 2015-12-16. An algorithm for the multivariate group lasso with covariance estimation. https://arxiv.org/abs/1512.05153

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