Minimum phi-divergence estimator and phi-divergence statistics in generalized linear models with binary data

Abstract

In this paper, we assume that the data are distributed according to a binomial distribution whose probabilities follow a generalized linear model. To fit the data the minimum phi-divergence estimator is studied as a generalization of the maximum likelihood estimator. We use the minimum phi-divergence estimator, which is the basis of some new statistics, for solving the problems of testing in a generalized linear model with binary data. A wide simulation study is carried out for studying the behavior of the new family of estimators as well as of the new family of test statistics.