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Model selection for estimating the non zero components of aGaussian vector
Published online by Cambridge University Press: 09 March 2006
Abstract
We propose a method based on a penalised likelihood criterion, forestimating the number on non-zero components of the meanof a Gaussian vector. Following the work of Birgé and Massart in Gaussian modelselection, we choose the penalty function such that the resultingestimator minimises the Kullback risk.
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- © EDP Sciences, SMAI, 2006
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