Stability-Selection via Correlated Resampling for Beta-Regression Models R package SelectBoost.beta version 0.4.5 Classification/MSC: 62H11, 62J12, 62J99 Adds variable-selection functions for Beta regression models (both mean and phi submodels) so they can be used within the 'SelectBoost' algorithm. Includes stepwise AIC, BIC, and corrected AIC on betareg() fits, 'gamlss'-based LASSO/Elastic-Net, a pure 'glmnet' iterative re-weighted least squares-based selector with an optional standardization speedup, and 'C++' helpers for iterative re-weighted least squares working steps and precision updates. Also provides a fastboost_interval() variant for interval responses, comparison helpers, and a flexible simulator simulation_DATA.beta() for interval-valued data. For more details see Bertrand and Maumy (2023) <doi:10.7490/f1000research.1119552.1>. Software Depends: R (>= 4.0) Imports: betareg, gamlss, gamlss.dist, glmnet, MASS, Rcpp, rlang, stats, withr LinkingTo: Rcpp, RcppArmadillo Suggests: future, future.apply, gamlss.lasso, ggplot2, knitr, rmarkdown, 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 2025-11-11 application/tgz https://CRAN.R-project.org/package=SelectBoost.beta doi:10.32614/CRAN.package.SelectBoost.beta