Titre :
|
Statistics for high-dimensional data : methods, theory and applications
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Auteurs :
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P. Bühlmann, - Auteur ;
S. Geer, - Auteur
|
Type de document :
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ouvrage
|
Editeur :
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London [GBR] : Springer, 2011
|
Collection :
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Springer Series in Statistics, ISSN 0172-7397
|
ISBN/ISSN/EAN :
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978-3-642-20191-2
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Format :
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1 vol. (XVII-556 p.) / Ill., graph., tabl. en noir et en coul. / 25 cm
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Langues:
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= Anglais
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Mots-clés:
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LISSAGE
;
PROGRAMMATION NON CONVEXE
;
VALEUR ABSOLUE
;
STATISTIQUE
;
MODELE LINEAIRE
|
Résumé :
|
Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, such as the Lasso and boosting methods. It also provides the mathematical theory behind them, proving their great potential in a large number of settings. Both the methods and theory are then illustrated with real data examples
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Note de contenu :
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Contient des exercices
|