mboost: Model-Based Boosting

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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.

Author
Torsten Hothorn [aut], Peter Buehlmann [aut], Thomas Kneib [aut], Matthias Schmid [aut], Benjamin Hofner [aut, cre], Fabian Sobotka [ctb], Fabian Scheipl [ctb]
Date of publication
2016-11-23 14:09:40
Maintainer
Benjamin Hofner <benjamin.hofner@pei.de>
License
GPL-2
Version
2.7-0
URLs

View on CRAN

Man pages

baselearners
Base-learners for Gradient Boosting
blackboost
Gradient Boosting with Regression Trees
boost_family-class
Class "boost\_family": Gradient Boosting Family
confint
Pointwise Bootstrap Confidence Intervals
control
Control Hyper-parameters for Boosting Algorithms
cvrisk
Cross-Validation
Family
Gradient Boosting Families
FP
Fractional Polynomials
gamboost
Gradient Boosting with Smooth Components
glmboost
Gradient Boosting with Component-wise Linear Models
IPCweights
Inverse Probability of Censoring Weights
mboost
Model-based Gradient Boosting
mboost_intern
Call internal functions.
mboost_package
mboost: Model-Based Boosting
methods
Methods for Gradient Boosting Objects
plot
Plot effect estimates of boosting models
stabsel
Stability Selection
survFit
Survival Curves for a Cox Proportional Hazards Model
varimp
Variable Importance

Files in this package

mboost
mboost/inst
mboost/inst/india_vcm.R
mboost/inst/mboost_Bioinf.R
mboost/inst/cache
mboost/inst/cache/bodyfat_benchmarks.rda
mboost/inst/cache/wpbc_benchmarks.rda
mboost/inst/cache/wpbc_survivalbenchmarks.rda
mboost/inst/cache/mboost_illustrations_benchmarks.R
mboost/inst/cache/curve_estimation.rda
mboost/inst/CITATION
mboost/inst/india_summary.R
mboost/inst/india_helpfunc.R
mboost/inst/NEWS.Rd
mboost/inst/india_preproc.R
mboost/inst/india_rqss_lambdaOptFunc.R
mboost/inst/India_quantiles.R
mboost/inst/india_additive.R
mboost/inst/readAML_Bullinger.R
mboost/inst/india_fit.R
mboost/inst/india_analysis.R
mboost/inst/birds_Biometrics.R
mboost/inst/india_plots.R
mboost/inst/india_rqssResults.R
mboost/inst/india_rqss.R
mboost/inst/doc
mboost/inst/doc/mboost_tutorial.R
mboost/inst/doc/mboost_tutorial.Rnw
mboost/inst/doc/mboost_illustrations.pdf
mboost/inst/doc/mboost.R
mboost/inst/doc/mboost.Rnw
mboost/inst/doc/mboost_tutorial.pdf
mboost/inst/doc/SurvivalEnsembles.R
mboost/inst/doc/mboost_illustrations.R
mboost/inst/doc/mboost_illustrations.Rnw
mboost/inst/doc/SurvivalEnsembles.pdf
mboost/inst/doc/SurvivalEnsembles.Rnw
mboost/inst/doc/mboost.pdf
mboost/inst/india_blackboost.R
mboost/inst/india_stumps.R
mboost/src
mboost/src/Makevars
mboost/src/mboost.c
mboost/NAMESPACE
mboost/R
mboost/R/bolscw.R
mboost/R/buser.R
mboost/R/btree.R
mboost/R/varimp.R
mboost/R/helpers.R
mboost/R/mboost.R
mboost/R/family.R
mboost/R/plot.R
mboost/R/control.R
mboost/R/crossvalidation.R
mboost/R/methods.R
mboost/R/stabsel.R
mboost/R/brad.R
mboost/R/bkronecker.R
mboost/R/confint.R
mboost/R/survival.R
mboost/R/bl.R
mboost/R/mboost_intern.R
mboost/R/bmrf.R
mboost/R/bmono.R
mboost/R/AAA.R
mboost/vignettes
mboost/vignettes/mboost_tutorial.Rnw
mboost/vignettes/jmlr2e.sty
mboost/vignettes/boost.bib
mboost/vignettes/mboost.Rnw
mboost/vignettes/setup.R
mboost/vignettes/mboost_illustrations.Rnw
mboost/vignettes/mboost_tutorial.bib
mboost/vignettes/SurvivalEnsembles.Rnw
mboost/README.md
mboost/MD5
mboost/build
mboost/build/vignette.rds
mboost/DESCRIPTION
mboost/man
mboost/man/Family.Rd
mboost/man/mboost_package.Rd
mboost/man/stabsel.Rd
mboost/man/survFit.Rd
mboost/man/IPCweights.Rd
mboost/man/mboost.Rd
mboost/man/blackboost.Rd
mboost/man/confint.Rd
mboost/man/cvrisk.Rd
mboost/man/control.Rd
mboost/man/varimp.Rd
mboost/man/glmboost.Rd
mboost/man/mboost_intern.Rd
mboost/man/baselearners.Rd
mboost/man/methods.Rd
mboost/man/gamboost.Rd
mboost/man/FP.Rd
mboost/man/plot.Rd
mboost/man/boost_family-class.Rd
mboost/cleanup