Um novo modelo de regressão para dados em Z

Abstract

There are several practical situations in which it is of interest to model events associated with discrete-valued variables. Until now, theories that have been constructed and re ned to handling observations of this nature have an emphasis on modeling nonnegative discrete data. Nevertheless, discrete observations that may assume any value on the set of integers Z = {. . . , −2, −1, 0, 1, 2, . . .} can also be found in di erent contexts. The main objective of this master thesis are to propose a new parameterization for the skew discrete Laplace distribution (KOZUBOWSKI; INUSAH, 2006), in terms of the mean and a dispersion parameter, and then de ne a new regression model able of modeling observations that assume values on Z based on this distribution. We consider the maximum likelihood estimator for the estimation of unknown model parameters. We propose diagnostic methods to evaluate the goodness of t. We performed some simulation studies to verify the performance of the proposed estimators, test statistics and residuals. Finally, we apply the model to two real data sets.