ABSTRACT
This chapter provides an introduction to the Generalized additive models for location scale and shape (gamlss()) function. It shows how the information stored in a gamlss class object can be used. The chapter explores some of the functions associated with gamlss class objects. There are two ways in which the user can weight observations out of an analysis. The first relies on the subset() function and can be used in the data argument of gamlss(). The second way is through the weights argument. The weights do not behave in the same way as in the glm() or lm() functions. In those functions they are prior weights used to fit only the mean of the model, while in gamlss() the same weights are applied for fitting all distribution parameters. The weights can be used for a weighted likelihood analysis where the contribution of the observations to the log-likelihood is weighted according to weights.
