Statistics for high-dimensional data : methods, theory and applications
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, provin...
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| Auteurs principaux: | , , |
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| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
2011.
Cham : Springer Nature |
| Collection: | Springer Series in Statistics
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| Sujets: | |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Description d'après consultation du 22 avril 2013 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Statistics for high-dimensional data, methods, theory and applications, Peter Bühlmann, Sara van de Geer, 2011, Berlin, Springer, 1 vol. (XVII-556 p.), Springer series in statistics, 978-3-642-20191-2 |