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Field name	Details
Dewey Class	519.5 (DDC 23)
Title	Statistics for High-Dimensional Data (EB) : Methods, Theory and Applications / by Peter Bühlmann, Sara van de Geer.
Author	Bühlmann, Peter
Added Personal Name	van de Geer, Sara author.
Other name(s)	SpringerLink (Online service)
Publication	Berlin, Heidelberg : Springer , 2011.
Physical Details	XVII, 556p. 31 illus., 8 illus. in color. : online resource.
Series	Springer Series in Statistics 0172-7397
ISBN	9783642201929
Summary Note	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 methodsâ 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.:
Contents note	Introduction -- Lasso for linear models -- Generalized linear models and the Lasso -- The group Lasso -- Additive models and many smooth univariate functions -- Theory for the Lasso -- Variable selection with the Lasso -- Theory for l1/l2-penalty procedures -- Non-convex loss functions and l1-regularization -- Stable solutions -- P-values for linear models and beyond -- Boosting and greedy algorithms -- Graphical modeling -- Probability and moment inequalities -- Author Index -- Index -- References -- Problems at the end of each chapter.
System details note	Online access is restricted to subscription insitutions through IP address (only for SISSA internal users)
Internet Site	http://dx.doi.org/10.1007/978-3-642-20192-9
Links to Related Works	Subject References: Computer Science . Mathematical Statistics . Probability and Statistics in Computer Science . Statistical Theory and Methods . Statistics . Authors: Bühlmann, Peter . van de Geer, Sara . Corporate Authors: SpringerLink (Online service) . Series: Springer Series in Statistics . Classification: 519.5 (DDC 23) .

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Statistics for High-Dimensional Data: Methods, Theory and Applications

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