Statistics for High-Dimensional Data Statistics for High-Dimensional Data
Springer Series in Statistics

Statistics for High-Dimensional Data

Methods, Theory and Applications

    • $129.99
    • $129.99

Publisher Description

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.

GENRE
Science & Nature
RELEASED
2011
June 8
LANGUAGE
EN
English
LENGTH
576
Pages
PUBLISHER
Springer Berlin Heidelberg
SELLER
Springer Nature B.V.
SIZE
14.7
MB
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