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RRBoost  

A Robust Boosting Algorithm
View on CRAN: Click here


Download and install RRBoost package within the R console
Install from CRAN:
install.packages("RRBoost")

Install from Github:
library("remotes")
install_github("cran/RRBoost")

Install by package version:
library("remotes")
install_version("RRBoost", "0.2")



Attach the package and use:
library("RRBoost")
Maintained by
Xiaomeng Ju
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-10-13
Latest Update: 2024-11-19
Description:
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) (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) ) and Robloss (Lutz et al. (2008) ).
How to cite:
Xiaomeng Ju (2020). RRBoost: A Robust Boosting Algorithm. R package version 0.2, https://cran.r-project.org/web/packages/RRBoost. Accessed 06 Aug. 2026.
Previous versions and publish date:
(2026-07-09 08:20), 0.1 (2020-10-13 15:10)
Other packages that cited RRBoost R package
View RRBoost citation profile
Other R packages that RRBoost depends, imports, suggests or enhances
Complete documentation for RRBoost
Functions, R codes and Examples using the RRBoost R package
Some associated functions: Boost.control . Boost . Boost.validation . airfoil . cal_imp_func . cal_predict . 
Some associated R codes: Boost.R . airfoil.R . loss-functions.R . user_rpart.R . utilities.R .  Full RRBoost package functions and examples
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