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High-dimensional gaussian model selection on a gaussian design

Nicolas Verzelen — 2010

Annales de l'I.H.P. Probabilités et statistiques

We consider the problem of estimating the conditional mean of a real gaussian variable =∑=1 + where the vector of the covariates ( )1≤≤ follows a joint gaussian distribution. This issue often occurs when one aims at estimating the graph or the distribution of a gaussian graphical model. We introduce a general model selection procedure which is based on the minimization of a penalized least squares type criterion. It handles...

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