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GPLTR: Generalized Partially Linear Tree-Based Regression Model

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. See 'Cyprien Mbogning et al.'(2014)<doi:10.1186/2043-9113-4-6> and 'Cyprien Mbogning et al.'(2015)<doi:10.1159/000380850> for an overview of all the methods implemented in this package.

Version: 1.5
Depends: rpart , parallel
Published: 2024-03-28
Author: Cyprien Mbogning and Wilson Toussile
Maintainer: Cyprien Mbogning <cyprien.mbogning at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
NeedsCompilation: no
CRAN checks: GPLTR results

Documentation:

Reference manual: GPLTR.pdf
Vignettes: intro

Downloads:

Package source: GPLTR_1.5.tar.gz
Windows binaries: r-devel: GPLTR_1.5.zip, r-release: GPLTR_1.5.zip, r-oldrel: GPLTR_1.5.zip
macOS binaries: r-release (arm64): GPLTR_1.5.tgz, r-oldrel (arm64): GPLTR_1.5.tgz, r-release (x86_64): GPLTR_1.5.tgz, r-oldrel (x86_64): GPLTR_1.5.tgz
Old sources: GPLTR archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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