globalboosttest: Testing the additional predictive value of high-dimensional data
Version 1.1-0

'globalboosttest' implements a permutation-based testing procedure to globally test the (additional) predictive value of a large set of predictors given that a small set of predictors is already available. Currently, 'globalboosttest' supports binary outcomes (via logistic regression) and survival outcomes (via Cox regression). It is based on boosting regression as implemented in the package 'mboost'.

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AuthorAnne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>, Torsten Hothorn <torsten.hothorn@stat.uni-muenchen.de>.
Date of publication2012-10-29 08:58:54
MaintainerAnne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>
LicenseGPL (>= 2)
Version1.1-0
URL
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("globalboosttest")

Man pages

globalboosttest: Testing the additional predictive value of high-dimensional...
globalboosttest-internal: Internal globalboosttest Functions
simdatabin: Simulated data with binary outcome
simdatasurv: Simulated data with survival outcome

Functions

globalboosttest Man page Source code
perm Man page Source code
simdatabin Man page
simdatasurv Man page

Files

data
data/simdatabin.RData
data/simdatasurv.RData
NAMESPACE
man
man/simdatabin.Rd
man/globalboosttest.Rd
man/globalboosttest-internal.Rd
man/simdatasurv.Rd
DESCRIPTION
MD5
R
R/globalboosttest.r
globalboosttest documentation built on May 19, 2017, 1:13 p.m.