### 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 80 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, lasso 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), the neural network function nnet() (of package nnet) and decision threes (of package rpart).

### 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

Three books on GAMLSS are in preparation: i) Flexible Regression and Smoothing, the GAMLSS packages in R. ii) Distributions for Location Scale and Shape, the GAMLSS implementation in R iii) Generalised Additive Models for Location Scale and Shape: Classical, Bayesian and Boosting Approaches. Draft versions of the first two books and other booklets can be found in Books & Articles The GAMLSS article on the Journal of Statistical Software can be useful for a short introduction and finally the short course booklets.

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