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Statistics for High-Dimensional Data: Methods, Theory and Applications (Springer Series in Statistics) (in English)
Peter Bühlmann; Sara Van De Geer (Author)
·
Springer
· Hardcover
Statistics for High-Dimensional Data: Methods, Theory and Applications (Springer Series in Statistics) (in English) - Peter Bühlmann; Sara Van De Geer
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Synopsis "Statistics for High-Dimensional Data: Methods, Theory and Applications (Springer Series in Statistics) (in English)"
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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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
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