Boosting Regression Quantiles
Overview
Boosting Regression Quantiles is a component-wise boosting algorithm, that embeds all boosting steps in the well-established framework of quantile regression. It is initialized with the corresponding quantile, uses a quantile-specific learning rate, and uses quantile regression as its base learner. The package implements this algorithm and allows cross-validation and stability selection.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK14 OK2026-03-10
Documentation
- Help pages
- 16
- Examples that run
- 100%16 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
- PRs merged (all time)
- not measured
- Median days to close, 50 most recently updated closed issues
- 26
- Median days to close, 50 most recently updated closed PRs
- not measured
Stars over time
Issues over time
4 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/stefanlinner/boostrq on 2026-10-22.
Dependencies
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.0.0Latest2024-03-05 · current release
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2024-03-05
- Total releases
- 1 / 2 yrs
- License
- GPL (>= 2) OSI
- Download size
- 19 KB
Cite
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