Statistics for High-Dimensional Data: Methods, Theory and Applications (Springer Series in Statistics)

Bühlmann, Peter; Van De Geer, Sara

ISBN 10: 3642201911 / ISBN 13: 9783642201912

Edité par Springer, 2011

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N° de réf. du vendeur I-9783642201912

Détails bibliographiques

• Titre: Statistics for High-Dimensional Data: Methods, Theory and Applications (Springer Series in Statistics)
• Éditeur: Springer
• Date de parution: 2011
• Langue: anglais
• ISBN à 10 chiffres: 3642201911
• ISBN à 13 chiffres: 9783642201912
• Reliure: Couverture rigide
• État de l'article: New

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Synopsis

This valuable compendium of statistical methods features a unique combination of methodology, theory, algorithms and applications. It covers recently developed approaches to handling large and complex data sets, including the Lasso and boosting methods.

À propos de l?auteur

Peter Bühlmann is Professor of Statistics at ETH Zürich. His main research areas are high-dimensional statistical inference, machine learning, graphical modeling, nonparametric methods, and statistical modeling in the life sciences. He is currently editor of the Annals of Statistics. He was awarded a Medallion lecture by the Institute of Mathematical Statistics in 2009 and read a paper to the Royal Statistical Society in 2010.

Sara van de Geer has been a full professor at the ETH in Zürich since 2005. Her main areas of research are empirical process theory, statistical learning theory, and nonparametric and high-dimensional statistics. She is an associate editor of Probability Theory and Related Fields, The Scandinavian Journal of Statistics and Statistical Surveys and a member of the Swiss National Science Foundation and correspondent of the Dutch Royal Academy of Sciences.
She received the IMS medal in 2003 and the ISI award in 2005, and was an invited speaker at the International Conference of Mathematicians in 2010.