boostrq: Boosting Regression Quantiles

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.

Version: 1.0.0
Depends: mboost, stabs, stats, parallel
Imports: quantreg, checkmate
Suggests: testthat (≥ 3.0.0)
Published: 2024-03-05
Author: Stefan Linner [aut, cre, cph]
Maintainer: Stefan Linner <stefan.linner97 at gmail.com>
BugReports: https://github.com/stefanlinner/boostrq/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/stefanlinner/boostrq
NeedsCompilation: no
Materials: README
CRAN checks: boostrq results

Documentation:

Reference manual: boostrq.pdf

Downloads:

Package source: boostrq_1.0.0.tar.gz
Windows binaries: r-prerel: boostrq_1.0.0.zip, r-release: boostrq_1.0.0.zip, r-oldrel: boostrq_1.0.0.zip
macOS binaries: r-prerel (arm64): boostrq_1.0.0.tgz, r-release (arm64): boostrq_1.0.0.tgz, r-oldrel (arm64): boostrq_1.0.0.tgz, r-prerel (x86_64): boostrq_1.0.0.tgz, r-release (x86_64): boostrq_1.0.0.tgz

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