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

By Peter Buhlmann, Sara Van de Geer, Peter Bühlmann

Book Overview

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.

• Format: Paperback
• Language: English
• ISBN: 3642268579
• ISBN13: 9783642268571
• Release Date: August 2013
• Publisher: Springer
• Length: 558 Pages
• Weight: 1.76 lbs.
• Dimensions: 1.2" x 6.2" x 9.2"