Distributions for Modeling Location, Scale, and Shape Using GAMLSS in R

"...focuses on all probability distributions that can be used in GAMLSS modelling...a distributional regression framework making inroads in different fields due to its flexibility...GAMLSS's power rests on its capability to apply smoothers to numeric and categorical covariates and model numeric response variables via probability distributions other than the usual exponential family...including continuous distributions, ...discrete distributions and mixtures of continuous and discrete (mixed) distributions...This last type of distribution, although commonplace in practice, is rather ignored by applied researchers...The book has three parts. Part II ("Advanced topics") contains eight Chapters, and is perhaps the most exciting section. It deals with topics that link the GAMLSS framework and probability distributions to 'hot' topics in statistical learning."
~ Fernando Marmolejo-Ramos, Raydonal Ospina, and Freddy Hernández-Barajas, respectively University of South Australia, Universidade Federal de Pernambuco, and Universidad Nacional de Colombia sede Medellín, appeared in Australian and New Zealand Journal of Statistics, September 2022