Statistics for High Dimensional Data is popular PDF and ePub book, written by Peter Bühlmann in 2011-06-08, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Statistics for High Dimensional Data can be Read Online from any device for your convenience.
Statistics for High Dimensional Data Book PDF Summary
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.
Detail Book of Statistics for High Dimensional Data PDF
- Author : Peter Bühlmann
- Release : 08 June 2011
- Publisher : Springer Science & Business Media
- ISBN : 9783642201929
- Genre : Mathematics
- Total Page : 558 pages
- Language : English
- PDF File Size : 16,7 Mb
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