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Statistics for high-dimensional data: methods, theory and applications
Statistics for high-dimensional data: methods, theory and applications
Author
Bühlmann, Peter
Publisher
Springer
Publication Date
c2011
Language
English
Book
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Table of Contents
From the Book
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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Subjects
Subjects
Least absolute deviations (Statistics)
Linear models (Statistics)
Mathematical statistics
Nonconvex programming
Smoothness of functions
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Contributors
Geer, S. A. van de
ISBN
9783642201912
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