A Robust Boosting Algorithm
Overview
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. It also implements previously proposed boosting algorithms in the simulation section of the paper: L2Boost, LADBoost, MBoost (Friedman, J. H. (2001) doi:10.1214/aos/1013203451) and Robloss (Lutz et al. (2008) doi:10.1016/j.csda.2007.11.006).
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 6
- Examples that run
- 50%3 run in a plain check · 3 never run
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 17%
Downloads
Dependencies
Installing RRBoost adds 7 packages (6 with compiled code, 5.7 MB of source tarballs). Heaviest: robustbase 2.2 MB, rrcov 1.5 MB, mvtnorm 1.0 MB.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 0.2Latest
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 0.12020-10-13
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2020-10-13
- Total releases
- 2 / 6 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 7.1 KB / 1 file
- Download size
- 23 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("RRBoost")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.