Statistics for High-Dimensional Data : Methods, Theory and Applications by Sara van de Geer
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Author: Sara van de Geer
Number of Pages: 558 pages
Published Date: 03 Aug 2013
Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Publication Country: Berlin, Germany
Language: English
ISBN: 9783642268571
Download Link: Statistics for High-dimensional Data Methods, Theory and Applications
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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. This in-depth approach highlights the methods' great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science.
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