Package: mboost
Title: Model-Based Boosting
Version: 2.1-1
Date: 2011-11-28
Author: Torsten Hothorn, Peter Buehlmann, Thomas Kneib, Matthias Schmid and
  Benjamin Hofner
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
Description: Functional gradient descent algorithm
  (boosting) for optimizing general risk functions utilizing
  component-wise (penalised) least squares estimates or regression
  trees as base-learners for fitting generalized linear, additive
  and interaction models to potentially high-dimensional data.
Depends: R (>= 2.10.0), methods, stats
Imports: Matrix, survival, splines, lattice
Suggests: multicore, party (>= 0.9-9993), ipred, MASS, fields, BayesX,
        gbm
LazyLoad: yes
LazyData: yes
License: GPL-2
Packaged: 2011-11-28 13:47:44 UTC; hothorn
Repository: CRAN
Date/Publication: 2011-11-29 07:30:55
