GPLTR: Generalized Partially Linear Tree-Based Regression Model
Version 1.2

Combining a generalized linear model with an additional tree part on the same scale. A four-step procedure is proposed to fit the model and test the joint effect of the selected tree part while adjusting on confounding factors. We also proposed an ensemble procedure based on the bagging to improve prediction accuracy and computed several scores of importance for variable selection.

Browse man pages Browse package API and functions Browse package files

AuthorCyprien Mbogning <cyprien.mbogning@inserm.fr> and Wilson Toussile
Date of publication2015-06-18 18:00:14
MaintainerCyprien Mbogning <cyprien.mbogning@gmail.com>
LicenseGPL (>= 2.0)
Version1.2
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("GPLTR")

Man pages

bag.aucoob: AUC on the Out Of Bag samples
bagging.pltr: bagging pltr models
best.tree.BIC.AIC: Prunning the Maximal tree
best.tree.bootstrap: parametric bootstrap on a pltr model
best.tree.CV: Prunning the Maximal tree
best.tree.permute: permutation test on a pltr model
burn: burn dataset
data_pltr: gpltr data example
GPLTR-package: Fit a generalized partially linear tree-based regression...
nested.trees: compute the nested trees
pltr.glm: Partially tree-based regression model function
predict_bagg.pltr: prediction on new features
predict_pltr: prediction
p.val.tree: Compute the p-value
tree2glm: tree to GLM
tree2indicators: From a tree to indicators (or dummy variables)
VIMPBAG: score of importance for variables

Functions

GPLTR Man page
GPLTR-package Man page
VARIMPPERM Source code
VIMPBAG Man page Source code
bag.aucoob Man page Source code
bagging.pltr Man page Source code
best.tree.BIC.AIC Man page Source code
best.tree.CV Man page Source code
best.tree.bootstrap Man page Source code
best.tree.permute Man page Source code
burn Man page
chenIMP Source code
data_pltr Man page
depthvar Source code
logistic.eval Source code
logistic.init Source code
logistic.split Source code
nested.trees Man page Source code
norm2 Source code
p.val.tree Man page Source code
pltr.glm Man page Source code
predict_bagg.pltr Man page Source code
predict_pltr Man page Source code
tree2glm Man page Source code
tree2indicators Man page Source code

Files

inst
inst/doc
inst/doc/intro.R
inst/doc/GPLTR-manual.pdf
inst/doc/intro.pdf
inst/doc/intro.Rnw
NAMESPACE
data
data/data_pltr.rda
data/burn.rda
R
R/tree2glm.R
R/norm2.R
R/best.tree.permute.R
R/Logistic_Split_Rpart.R
R/Imp_Score.R
R/best.tree.CV.R
R/pltr.glm.R
R/bagging.pltr.R
R/predict_bagg.pltr.R
R/nested.trees.R
R/tree2indicators.R
R/best.tree.BIC.AIC.R
R/p.val.tree.R
R/best.tree.bootstrap.R
R/bag.aucoob.R
R/predict_pltr.R
vignettes
vignettes/Bibliopltr.bib
vignettes/intro.Rnw
MD5
build
build/vignette.rds
DESCRIPTION
man
man/best.tree.bootstrap.Rd
man/burn.Rd
man/tree2glm.Rd
man/predict_pltr.Rd
man/bag.aucoob.Rd
man/GPLTR-package.Rd
man/best.tree.CV.Rd
man/predict_bagg.pltr.Rd
man/p.val.tree.Rd
man/best.tree.permute.Rd
man/VIMPBAG.Rd
man/best.tree.BIC.AIC.Rd
man/bagging.pltr.Rd
man/pltr.glm.Rd
man/nested.trees.Rd
man/tree2indicators.Rd
man/data_pltr.Rd
GPLTR documentation built on May 19, 2017, 6:26 p.m.