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

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

Paperback

Series: Springer Statistics

ApplicationsGeneral ComputersProbability & Statistics

ISBN10: 3642268579
ISBN13: 9783642268571
Publisher: Springer
Published: Aug 3 2013
Pages: 558
Weight: 1.76
Height: 1.17 Width: 6.17 Depth: 9.17
Language: English
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.

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