Package: mboost
Title: Model-Based Boosting
Version: 2.4-2
Date: 2015-02-12
Authors@R: c(person("Torsten", "Hothorn", role = c("aut", "cre"),
                    email = "Torsten.Hothorn@R-project.org"),
             person("Peter", "Buehlmann", role = "aut"),
             person("Thomas", "Kneib", role = "aut"),
             person("Matthias", "Schmid", role = "aut"),
             person("Benjamin", "Hofner", role = "aut"),
             person("Fabian", "Sobotka", role = "ctb"),
             person("Fabian", "Scheipl", role = "ctb"))
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 (>= 2.14.0), methods, stats, parallel, stabs (>= 0.5-0)
Imports: Matrix, survival, splines, lattice, nnls, quadprog, utils
Suggests: party (>= 1.0-3), TH.data, MASS, fields, BayesX, gbm,
        mlbench, RColorBrewer, rpart (>= 4.0-3), randomForest, nnet
LazyData: yes
License: GPL-2
URL: http://mboost.r-forge.r-project.org/
Packaged: 2015-02-12 15:30:11 UTC; bhofner
Author: Torsten Hothorn [aut, cre],
  Peter Buehlmann [aut],
  Thomas Kneib [aut],
  Matthias Schmid [aut],
  Benjamin Hofner [aut],
  Fabian Sobotka [ctb],
  Fabian Scheipl [ctb]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2015-02-12 18:47:04
