Statistics for High-Dimensional Data Methods, Theory and Applications by Peter Bühlmann and Sara van de Geer

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Statistics for High-Dimensional Data Methods, Theory and Applications by Peter Bühlmann and Sara van de Geer
Statistics for High-Dimensional data: Methods, Theory and Applications (Springer Series in Statistics) by Peter Bühlmann and Sara van de Geer
English | June 14, 2011 | ISBN: 3642201911 | 575 Pages | PDF | 5 MB

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, including the Lasso and versions of it for various models, boosting methods



, undirected graphical modeling, and procedures controlling false positive selections.
A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples.




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Tags: Statistics, Dimensional, Methods, Theory, Applications, hlmann

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