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; firstname.lastname@example.org
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
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.