Statistics for High-Dimensional Data, Methods, Theory and Applications View Full Text


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Book Info

DATE

2011

GENRE

Monograph

AUTHORS

Peter Bühlmann , Sara van de Geer

PUBLISHER

Springer Nature

ABSTRACT

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. More... »

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-20192-9

DOI

http://dx.doi.org/10.1007/978-3-642-20192-9

ISBN

978-3-642-20191-2 | 978-3-642-20192-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1039594045


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