SelectBoost.beta

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.

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