Download the fantastic book titled Statistics for High Dimensional Data written by Peter Bühlmann, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Statistics for High Dimensional Data", which was released on 08 June 2011. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Mathematics genre.
Summary of Statistics for High Dimensional Data by Peter Bühlmann PDF
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 About Statistics for High Dimensional Data PDF
- Author : Peter Bühlmann
- Publisher : Springer Science & Business Media
- Genre : Mathematics
- Total Pages : 558 pages
- ISBN : 364220192X
- Release Date : 08 June 2011
- PDF File Size : 36,6 Mb
- Language : English
- Rating : 4/5 from 21 reviews
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