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 |
| Reference manual: | boostrq.pdf |
| Package source: | boostrq_1.0.0.tar.gz |
| Windows binaries: | r-devel: boostrq_1.0.0.zip, r-release: boostrq_1.0.0.zip, r-oldrel: boostrq_1.0.0.zip |
| macOS binaries: | r-release (arm64): boostrq_1.0.0.tgz, r-oldrel (arm64): boostrq_1.0.0.tgz, r-release (x86_64): boostrq_1.0.0.tgz, r-oldrel (x86_64): boostrq_1.0.0.tgz |
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