# Model selection for estimating the non zero components of a Gaussian vector

ESAIM: Probability and Statistics (2006)

- Volume: 10, page 164-183
- ISSN: 1292-8100

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topHuet, Sylvie. "Model selection for estimating the non zero components of a Gaussian vector." ESAIM: Probability and Statistics 10 (2006): 164-183. <http://eudml.org/doc/249747>.

@article{Huet2006,

abstract = {
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.
},

author = {Huet, Sylvie},

journal = {ESAIM: Probability and Statistics},

keywords = {Kullback risk; model selection; penalised likelihood criteria.; penalised likelihood criteria},

language = {eng},

month = {3},

pages = {164-183},

publisher = {EDP Sciences},

title = {Model selection for estimating the non zero components of a Gaussian vector},

url = {http://eudml.org/doc/249747},

volume = {10},

year = {2006},

}

TY - JOUR

AU - Huet, Sylvie

TI - Model selection for estimating the non zero components of a Gaussian vector

JO - ESAIM: Probability and Statistics

DA - 2006/3//

PB - EDP Sciences

VL - 10

SP - 164

EP - 183

AB -
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.

LA - eng

KW - Kullback risk; model selection; penalised likelihood criteria.; penalised likelihood criteria

UR - http://eudml.org/doc/249747

ER -

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