Statistics for High Dimensional Data Methods Theory and Applications 1st edition by Peter Bühlmann, Sara van de Geer ISBN 364220192X 9783642201929

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Product details:

ISBN 10: 364220192X
ISBN 13: 9783642201929
Author:  Peter Bühlmann, Sara van de Geer

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.

Statistics for High Dimensional Data Methods Theory and Applications 1st Table of contents:

Chapter 1 Introduction
Chapter 2 Lasso for near models
Chapter 3 Generalized linear models and the Lasso
Chapter 4 The group Lasso
Chapter 5 Additive models and many smooth univariate functions
Chapter 6 Theory for the Lasso
Chapter 7 Variable selection with the Lasso
Chapter 8 Theory for 11 12penalty procedures
Chapter 9 Nonconvex loss functions and regularization

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Tags: Peter Bühlmann, Sara van de Geer, High Dimensional, Methods Theory