Stability-Selection via Correlated Resampling for 'GAMLSS' Models R package SelectBoost.gamlss version 0.2.2 Classification/MSC: 62H11, 62J12, 62J99 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. Software Depends: R (>= 4.1.0) Imports: gamlss, Rcpp, rlang, SelectBoost, stats, utils LinkingTo: Rcpp, RcppArmadillo Suggests: doParallel, foreach, future, future.apply, gamlss.data, gamlss.dist, ggplot2, glmnet, grpreg, knitr, knockoff, MASS, microbenchmark, nlme, parallel, pkgdown, pscl, rmarkdown, SGL, testthat (>= 3.0.0) Frederic Bertrand <frederic.bertrand@lecnam.net> Comprehensive R Archive Network (CRAN) Frederic Bertrand [cre, aut] (ORCID: <https://orcid.org/0000-0002-0837-8281>) GPL-3 2025-11-25 application/tgz https://CRAN.R-project.org/package=SelectBoost.gamlss doi:10.32614/CRAN.package.SelectBoost.gamlss