Author | : Peter Bühlmann |
File Size | : 45,9 Mb |
Publisher | : Springer Science & Business Media |
Language | : English |
Release Date | : 08 June 2011 |
ISBN | : 9783642201929 |
Pages | : 558 pages |
Statistics for High Dimensional Data by Peter Bühlmann 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.