Statistics for high-dimensional data : methods, theory and applications / Peter Bühlmann, Sara van de Geer.
By: Bühlmann, Peter.
Contributor(s): Geer, S. A. van de (Sara A.).
Series: Springer series in statistics: Publisher: Heidelberg ; New York : Springer, c2011Description: xvii, 556 p. : ill. (some col.) ; 24 cm.ISBN: 9783642201912 (hdbk. : acidfree paper); 3642201911 (hdbk. : acidfree paper).Subject(s): Mathematical statistics | Smoothness of functions | Nonconvex programming | Least absolute deviations (Statistics) | Linear models (Statistics)Online resources: Full-text hereItem type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Book | Skoltech library Shelves | QA276 .B84 2011 (Browse shelf) | Available | 2000006547 |
Browsing Skoltech library Shelves , Shelving location: Shelves Close shelf browser
QA274.7 .P88 1994 Markov decision processes : | QA274.7 .P88 1994 Markov decision processes : | QA275 .H38 2015 Statistical learning with sparsity : | QA276 .B84 2011 Statistics for high-dimensional data : | QA276 .D3254 2008 Asymptotic theory of statistics and probability / | QA276 .G57 2015 Introduction to high-dimensional statistics / | QA276 .H59 2013 Introduction to mathematical statistics / |
Includes bibliographical references (p. 547-556) and indexes.
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-regulation -- Stable solutions -- P-values for linear models and beyond -- Boosting and greedy algorithms -- Graphical modeling -- Probabililty and moment inequalities.
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