Package: RRBoost 0.2

Xiaomeng Ju

RRBoost: A Robust Boosting Algorithm

An implementation of robust boosting algorithms for regression in R. This includes the RRBoost method proposed in the paper "Robust Boosting for Regression Problems" (Ju X and Salibian-Barrera M. 2020) <doi:10.1016/j.csda.2020.107065> (to appear in Computational Statistics and Data Science). It also implements previously proposed boosting algorithms in the simulation section of the paper: L2Boost, LADBoost, MBoost (Friedman, J. H. (2001) <10.1214/aos/1013203451>) and Robloss (Lutz et al. (2008) <10.1016/j.csda.2007.11.006>).

Authors:Xiaomeng Ju [aut,cre], Matias Salibian-Barrera [aut],

RRBoost_0.2.tar.gz
RRBoost_0.2.zip(r-4.5)RRBoost_0.2.zip(r-4.4)RRBoost_0.2.zip(r-4.3)
RRBoost_0.2.tgz(r-4.5-any)RRBoost_0.2.tgz(r-4.4-any)RRBoost_0.2.tgz(r-4.3-any)
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RRBoost.pdf |RRBoost.html
RRBoost/json (API)

# Install 'RRBoost' in R:
install.packages('RRBoost', repos = c('https://xmengju.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/xmengju/rrboost/issues

Datasets:

On CRAN:

Conda-Forge:

2.70 score 3 scripts 558 downloads 5 exports 9 dependencies

Last updated 4 months agofrom:ef15a53be8. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 17 2025
R-4.5-winOKFeb 17 2025
R-4.5-macOKFeb 17 2025
R-4.5-linuxOKFeb 17 2025
R-4.4-winOKFeb 17 2025
R-4.4-macOKFeb 17 2025
R-4.3-winOKFeb 17 2025
R-4.3-macOKFeb 17 2025

Exports:BoostBoost.controlBoost.validationcal_imp_funccal_predict

Dependencies:DEoptimRlatticemvtnormpcaPPpyinitRobStatTMrobustbaserpartrrcov