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

2011 ed.

Book Details

Format Paperback / Softback
ISBN-10 3642268579
ISBN-13 9783642268571
Edition 2011 ed.
Publisher Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Country of Manufacture DE
Country of Publication GB
Publication Date Aug 3rd, 2013
Print length 558 Pages
Weight 842 grams
Dimensions 16.00 x 28.70 x 3.90 cms
Ksh 17,350.00
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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.

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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