DIAGNOSTICS IN LOG-LINEAR MODELS
In this paper, we study the diagnostics of a generalized linear model. The model is fitted using the maximum likelihood method and the deletion of observation technique is used to identify outliers. Expressions for the change in the estimates of the parameters after re-fitting are obtained. A count data model is cited as an illustration.
generalized linear model, maximum likelihood estimator, deletion technique.