Interface for extra smooth functions including tensor products, 
             neural networks and decision trees.

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>.

This is an add-on package to GAMLSS. The purpose of this
        package is to allow users to fit interval response variables in
        GAMLSS models. The main function gen.cens() generates a
        censored version of an existing GAMLSS family distribution.

Data used as examples in the books on Generalized Additive Models for Location Scale and Shape:
  Stasinopoulos, Rigby, Heller, Voudouris, De Bastiani (2017). Flexible Regression and Smoothing: Using GAMLSS in R, <doi:10.1201/b21973>.
  Rigby, Stasinopoulos, Heller, De Bastiani (2019). Distributions for Modeling Location, Scale, and Shape Using GAMLSS in R, <doi:10.1201/9780429298547>.
  Stasinopoulos, Kneib, Klein, Mayr, Heller (2024). Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications, <doi:10.1017/9781009410076>.

Demos for smoothing and gamlss.family distributions.

A set of distributions which can be used for modelling the response variables in Generalized Additive Models for Location Scale and Shape, Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The distributions can be continuous, discrete or mixed distributions. Extra distributions can be created, by transforming, any continuous distribution defined on the real line, to a distribution defined on ranges 0 to infinity or 0 to 1, by using a 'log' or a 'logit' transformation respectively.

Computational intensive calculations for Generalized Additive Models for Location Scale and Shape, <doi:10.1111/j.1467-9876.2005.00510.x>.

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.