Volume 10, September 2006
|Page(s)||164 - 183|
|Published online||09 March 2006|
Model selection for estimating the non zero components of a Gaussian vector
INRA, MIA, 78352 Jouy-en-Josas Cedex, France; email@example.com
Revised: 28 September 2005
We propose a method based on a penalised likelihood criterion, for estimating the number on non-zero components of the mean of a Gaussian vector. Following the work of Birgé and Massart in Gaussian model selection, we choose the penalty function such that the resulting estimator minimises the Kullback risk.
Mathematics Subject Classification: 62G05 / 62G09
Key words: Kullback risk / model selection / penalised likelihood criteria.
© EDP Sciences, SMAI, 2006
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