Springer Series in Statistics: Methods, Theory and Applications

Bühlmann, Peter; van de Geer, Sara

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.

Details

Published by: Springer

Publication Date: 2013-08-03

Format: Paperback

ISBN-13: 9783642268571

DOI: 10.1007/978-3-642-20192-9

Dimensions: 235cm x155cm

Pages: 558