Nonfiction | Computer & Technology

Statistics for High-Dimensional Data : Methods, Theory and Applications

by Peter Bühlmann

2020-05-28 14:00:28

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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... Read more

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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Book Details

File size9.1x6.3x1.3inches
Print pages556
PublisherSpringer
Publication date June 1, 2011
ISBN9783642201912
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Peter Bühlmann
Author
...

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