This is an add-on package to 'gamlss'. The purpose of this package is to allow users to fit GAMLSS (Generalised Additive Models for Location Scale and Shape) models when the response variable is defined either in the intervals [0,1), (0,1] and [0,1] (inflated at zero and/or one distributions), or in the positive real line including zero (zero-adjusted distributions). The mass points at zero and/or one are treated as extra parameters with the possibility to include a linear predictor for both. The package also allows transformed or truncated distributions from the GAMLSS family to be used for the continuous part of the distribution. Standard methods and GAMLSS diagnostics can be used with the resulting fitted object.

Interface for extra high-dimensional smooth functions for Generalized Additive Models for Location Scale and Shape (GAMLSS) including (adaptive) lasso, ridge, elastic net and least angle regression.

The main purpose of this package is to allow fitting of
        mixture distributions with generalised additive models for location 
        scale and shape models see Chapter 7 of Stasinopoulos et al. (2017) <doi:10.1201/b21973-4>.

It allows us to fit Gaussian Markov Random Field within the
    Generalized Additive Models for Location Scale and Shape algorithms.

This is an add on package to GAMLSS. The purpose of this
        package is to allow users to defined truncated distributions in
        GAMLSS models. The main function gen.trun() generates truncated
        version of an existing GAMLSS family distribution.

Density, distribution function, quantile function and random generation for the bimodal skew symmetric normal distribution of Hassan and El-Bassiouni (2016) <doi:10.1080/03610926.2014.882950>.

Fits generalized additive models for the location, scale and shape
    parameters of a generalized extreme value response distribution. The
    methodology is based on Rigby, R.A. and Stasinopoulos, D.M. (2005),
    <doi:10.1111/j.1467-9876.2005.00510.x> and implemented using functions from
    the 'gamlss' package <doi:10.32614/CRAN.package.gamlss>.