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penalised likelihood criteria.

ESAIM: Probability and Statistics (1)

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1 results

Model selection for estimating the non zero components of aGaussian vector
Sylvie Huet
Journal:

ESAIM: Probability and Statistics / Volume 10 / February 2006

Published online by Cambridge University Press:

09 March 2006, pp. 164-183

Print publication:

February 2006
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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.