Package: boostrq 1.0.0

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.

Authors:Stefan Linner [aut, cre, cph]

boostrq_1.0.0.tar.gz
boostrq_1.0.0.zip(r-4.7)boostrq_1.0.0.zip(r-4.6)boostrq_1.0.0.zip(r-4.5)
boostrq_1.0.0.tgz(r-4.6-any)boostrq_1.0.0.tgz(r-4.5-any)
boostrq_1.0.0.tar.gz(r-4.7-any)boostrq_1.0.0.tar.gz(r-4.6-any)
boostrq_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
boostrq/json (API)

# Install 'boostrq' in R:
install.packages('boostrq', repos = c('https://stefanlinner.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/stefanlinner/boostrq/issues

On CRAN:

Conda:

3.00 score 2 stars 3 scripts 179 downloads 2 exports 19 dependencies

Last updated from:f2d3480f8d. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK129
source / vignettesOK266
linux-release-x86_64OK125
macos-release-arm64OK203
macos-oldrel-arm64OK152
windows-develOK92
windows-releaseOK93
windows-oldrelOK92
wasm-releaseOK93

Exports:boostrqbrq

Dependencies:backportscheckmateFormulainumlatticelibcoinMASSMatrixMatrixModelsmboostmvtnormnnlspartykitquadprogquantregrpartSparseMstabssurvival