Generalized Partially Linear Tree-Based Regression Model
Overview
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.
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NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Cyprien Mbogning <cyprien.mbogning@gmail.com>’
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Authors@R: c(person(given = "Cyprien",
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email = "cyprien.mbogning@inserm.fr"),
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family = "Toussile",
role = "aut"))
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Documentation
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Maintainer since 0.85 (2014)
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- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.5Latest
- 1.42023-08-26 · diff ↗
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 1.32022-04-10 · diff ↗
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- RR 3.3.0 released · 2016-05-03
- 1.22015-06-18 · diff ↗
- RR 3.2.0 released · 2015-04-16
Package metadata
- First published
- 2014-04-23
- Total releases
- 7 / 12 yrs
- License
- GPL (>= 2.0)
- Bundled data
- 14 KB / 2 files
- Download size
- 404 KB
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