Package: SelectBoost.quantile 0.3.1

SelectBoost.quantile: 'SelectBoost'-Style Variable Selection for Quantile Regression

A 'SelectBoost'-inspired workflow for sparse quantile regression. The package builds correlation neighborhoods, perturbs correlated predictors with a directional sampler inspired by the original 'SelectBoost' internals, refits penalized quantile regression models on the perturbed designs, and aggregates variable-selection frequencies across a path of correlation thresholds.

Authors:Frederic Bertrand [cre, aut]

SelectBoost.quantile_0.3.1.tar.gz
SelectBoost.quantile_0.3.1.zip(r-4.7)SelectBoost.quantile_0.3.1.zip(r-4.6)SelectBoost.quantile_0.3.1.zip(r-4.5)
SelectBoost.quantile_0.3.1.tgz(r-4.6-any)SelectBoost.quantile_0.3.1.tgz(r-4.5-any)
SelectBoost.quantile_0.3.1.tar.gz(r-4.7-any)SelectBoost.quantile_0.3.1.tar.gz(r-4.6-any)
SelectBoost.quantile_0.3.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
SelectBoost.quantile/json (API)

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

Bug tracker:https://github.com/fbertran/selectboost.quantile/issues

Pkgdown/docs site:https://fbertran.github.io

On CRAN:

Conda:

4.60 score 1 stars 7 scripts 430 downloads 9 exports 13 dependencies

Last updated from:d4b7b09ae3. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK138
source / vignettesOK204
linux-release-x86_64OK122
macos-release-arm64OK120
macos-oldrel-arm64OK120
windows-develOK92
windows-releaseOK72
windows-oldrelOK93
wasm-releaseOK99

Exports:benchmark_quantile_selectiondefault_quantile_benchmark_scenariosgroup_componentsgroup_neighborsquantile_lasso_selectorselectboost_quantilesimulate_quantile_datasupport_selectboost_quantiletune_lambda_quantile

Dependencies:clueclusterlatticeMASSMatrixMatrixModelsmovMFquantregskmeansslamSparseMsurvivalwithr

Validation Study
Scope | Overall summary | Correlated but not high-dimensional regimes | High-dimensional stress regime | Reproducing the study
Rendered fromvalidation-study.Rmdusingknitr::rmarkdown

Last update: 2026-04-07
Started: 2026-03-29

Getting Started
Overview | Simulate a correlated design | Fit a first model | Summarize and extract stable support | Plot the frequency path | Formula interface and multiple quantiles | Inspect penalty tuning directly | Next steps
Rendered fromgetting-started.Rmdusingknitr::rmarkdown

Last update: 2026-04-01
Started: 2026-04-01