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Statistics for high-dimensional data : methods, theory and applications / by Peter Bühlmann, Sara van de Geer

By: Contributor(s): Material type: TextTextSeries: Publication details: New York : Springer, c2011.Description: xvii, 556p. : ill. (some col.)ISBN:
  • 9783642201912 (hdbk. : acidfree paper)
  • 3642201911 (hdbk. : acidfree paper)
Subject(s): DDC classification:
  • 519.5 BUH
Contents:
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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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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