Statistics for high-dimensional data :methods, theory and applications
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Heidelberg ; New York
Name of Publisher, Distributor, etc.
SPRINGER
Date of Publication, Distribution, etc.
c2011
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
xvii, 556 p. : ill. )some col.( ; 24 cm.
SERIES
Other Title Information
Springer series in statistics
NOTES PERTAINING TO TITLE AND STATEMENT OF RESPONSIBILITY
Text of Note
Peter Buhlmann, Sara van de Geer
CONTENTS NOTE
Text of Note
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 lb1s/lb2s-penalty procedures -- Non-convex loss functions and lb1s-regulation -- Stable solutions -- P-values for linear models and beyond -- Boosting and greedy algorithms -- Graphical modeling -- Probabililty and moment inequalities