Package: SelectBoost.gamlss 0.2.2

Frederic Bertrand

SelectBoost.gamlss: Stability-Selection via Correlated Resampling for 'GAMLSS' Models

Extends the 'SelectBoost' approach to Generalized Additive Models for Location, Scale and Shape (GAMLSS). Implements bootstrap stability-selection across parameter-specific formulas (mu, sigma, nu, tau) via gamlss::stepGAIC(). Includes optional standardization of predictors and helper functions for corrected AIC calculation. More details can be found in Bertrand and Maumy (2024) <https://hal.science/hal-05352041> that highlights correlation-aware resampling to improve variable selection for GAMLSS and quantile regression when predictors are numerous and highly correlated.

Authors:Frederic Bertrand [cre, aut]

SelectBoost.gamlss_0.2.2.tar.gz
SelectBoost.gamlss_0.2.2.tar.gz(r-4.7-arm64)SelectBoost.gamlss_0.2.2.tar.gz(r-4.7-x86_64)SelectBoost.gamlss_0.2.2.tar.gz(r-4.6-arm64)SelectBoost.gamlss_0.2.2.tar.gz(r-4.6-x86_64)
SelectBoost.gamlss_0.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SelectBoost.gamlss/json (API)
NEWS

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

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

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

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • boys7482 - Anthropometric measurements for Dutch boys

On CRAN:

Conda:

openblascppopenmp

3.95 score 20 scripts 148 downloads 20 exports 53 dependencies

Last updated from:b6dd3cfa11. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK143
linux-devel-x86_64OK171
source / vignettesOK342
linux-release-arm64OK192
linux-release-x86_64OK146
wasm-releaseOK196

Exports:.family_defaults.family_tolerance.gen_familyAICc_gamlssautoboost_gamlsscheck_fast_vs_genericconfidence_functionalsconfidence_tableeffect_plotfast_vs_generic_llfastboost_gamlssknockoff_filter_muknockoff_filter_paramplot_sb_gamlssplot_stability_curvessb_gamlsssb_gamlss_c0_gridSelectBoost_gamlssselection_tabletune_sb_gamlss

Dependencies:abindanimationCascadecliclustercodetoolscpp11curldeldirforeachgamlssgamlss.datagamlss.distglmnetglueigraphinterpiteratorsjpeglarslatticelatticeExtralifecyclelimmamagickmagrittrMASSMatrixmsgpsnlmennetnnlsnor1mixpkgconfigplspngRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRfastrlangSelectBoostshapesplsstatmodsurvivaltnetvarbvsvctrsVGAMzigg

Advanced Real Data Examples: Zero-Inflation, Semicontinuous, and Longitudinal Growth

Frédéric Bertrand

Rendered fromadvanced-real-data-examples.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2025-11-25
Started: 2025-11-25

Algorithmic Pseudocode for SelectBoost.gamlss

Frédéric Bertrand

Rendered fromalgorithm-pseudocode.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2025-11-25
Started: 2025-11-25

Benchmark: Stepwise vs Grouped vs Glmnet Engines

Frédéric Bertrand

Rendered frombenchmark.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2025-11-25
Started: 2025-11-25

Comparing SelectBoost-GAMLSS Variants

Frédéric Bertrand

Rendered fromcomparison.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2025-11-25
Started: 2025-11-25

Confidence Functionals for SelectBoost-GAMLSS

Frédéric Bertrand

Rendered fromconfidence-functionals.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2025-11-25
Started: 2025-11-25

Fast Deviance: Microbenchmarks

Frédéric Bertrand

Rendered fromfast-deviance-benchmark.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2025-11-25
Started: 2025-11-25

Fast Deviance: Numerical Equality Checks

Frédéric Bertrand

Rendered fromfast-deviance-equality.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2025-11-25
Started: 2025-11-25

Real Data Examples with Different Distributions

Frédéric Bertrand

Rendered fromreal-data-examples.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2025-11-25
Started: 2025-11-25

Stability-Selection for GAMLSS with SelectBoost.gamlss

Frédéric Bertrand

Rendered fromselectboost-gamlss.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2025-11-25
Started: 2025-11-25

Readme and manuals

Help Manual

Help pageTopics
Reasonable defaults.family_defaults
Per-family numeric tolerance for equality checks.family_tolerance
Try to generate values for a family.gen_family
AICc for a gamlss fitAICc_gamlss
AutoBoost for GAMLSS (SelectBoost-style)autoboost_gamlss
Anthropometric measurements for Dutch boys (1997 reference)boys7482
Numerical check: fast vs generic deviance log-likelihoodcheck_fast_vs_generic
Confidence functionals from a c0 gridconfidence_functionals
Compute SelectBoost-like confidence table across c0confidence_table
K-fold deviance for an sb_gamlss configurationcv_deviance_sb
One-variable effect plot from an sb_gamlss (or gamlss) fiteffect_plot print.effect_plot_failure
Compare fast vs generic deviance log-likelihood evaluationfast_vs_generic_ll
FastBoost for GAMLSS (lightweight stability selection)fastboost_gamlss
Get a density function for a gamlss familyget_density_fun
Knockoff filter for mu (approximate group control)knockoff_filter_mu
Knockoff filter for sigma/nu/tau (approximate group control)knockoff_filter_param
Log-likelihood (sum) on newdata given a gamlss fitloglik_gamlss_newdata
Plot selection frequencies for sb_gamlssplot_sb_gamlss
Plot stability curves p(c0) for selected termsplot_stability_curves
Plot confidence functionalsplot.sb_confidence
Plot selection proportions for a single sb_gamlssplot.SelectBoost_gamlss
Plot summary for sb_gamlss_c0_gridplot.SelectBoost_gamlss_grid
Predict distribution parameters on newdatapredict_params
SelectBoost for GAMLSS (stability selection)sb_gamlss
Stability curves over a c0 grid for sb_gamlsssb_gamlss_c0_grid
SelectBoost-style wrapper for GAMLSSplot.summary.SelectBoost_gamlss SelectBoost_gamlss summary.SelectBoost_gamlss
Selection table accessorselection_table
Tune select engines/penalties via a small stability runtune_sb_gamlss