In this paper we propose two efficient cyclic coordinate algorithms to estimate structured concentration matrix in penalized Gaussian graphical models. Symmetry restrictions on the concentration matrix are particularly useful to reduce the number of parameters to be estimated and to create specific structured graphs. The penalized Gaussian graphical models are suitable for high-dimensional data.

Abbruzzo, A., Augugliaro, L., Mineo, A., Wit, E. (2014). Cyclic coordinate for penalized Gaussian graphical models with symmetry restriction. In Proceedings in Computational Statistics.

Cyclic coordinate for penalized Gaussian graphical models with symmetry restriction

ABBRUZZO, Antonino;AUGUGLIARO, Luigi;MINEO, Angelo;
2014-01-01

Abstract

In this paper we propose two efficient cyclic coordinate algorithms to estimate structured concentration matrix in penalized Gaussian graphical models. Symmetry restrictions on the concentration matrix are particularly useful to reduce the number of parameters to be estimated and to create specific structured graphs. The penalized Gaussian graphical models are suitable for high-dimensional data.
2014
978-2-8399-1347-8
Abbruzzo, A., Augugliaro, L., Mineo, A., Wit, E. (2014). Cyclic coordinate for penalized Gaussian graphical models with symmetry restriction. In Proceedings in Computational Statistics.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/96091
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