### What is GAMLSS

GAMLSS are (semi) parametric univariate regression models, where all the parameters of the assumed distribution for the response can be modelled as additive functions of the explanatory variables

### How to use GAMLSS

The GAMLSS framework of statistical modelling is implemented in a series of packages in R. The packages can be downloaded from the R library, CRAN.

### What distributions can be used within GAMLSS

GAMLSS provide over 70 continuous, discrete and mixed distributions for modelling the response variable. Truncated, censored, log and logit transformed and finite mixture versions of these distributions can be also used.

### What additive terms can be used within GAMLSS

P-splines, Cubic splines, loess smoothing, ridge regression, simple random effects and varying coefficient models are some of the additive functions provided in the implementation. Appropriate interface is also provided so GAMLSS models can be used in combination with smoothers from the gam() function (of package mgcv) or the neural network function nnet() (of package nnet).

### Who's is using GAMLSS

GAMLSS has been used in a variety of fields including: actuarial science, biology, biosciences, energy economic, genomics, finance, fisheries, food consumption, growth curves estimation, marine research, medicine, meteorology, rainfalls, vaccines, e.t.c.

### How to learn more about GAMLSS

Two books on GAMLSS are in preparation: i) The Distribution Toolbox of GAMLSS and ii) GAMLSS Flexible Regression in R. Draft versions of the two books will available in the web soon. Meanwhile, the second edition of original manual provides information on how to use the R-package (dated), the GAMLSS article on the Journal of Statistical Software can be useful for a short introduction and finally the short course booklets.

## Versionn 4.2-7