In many applications, the response variable is not Normally distributed. GLM can be used to analyze data from various non-Normal distributions. In this short course, we will introduce two most common ...

This paper develops a class of models to deal with missing data from longitudinal studies. We assume that separate models for the primary response and missingness (e.g., number of missed visits) are ...

This is a preview. Log in through your library . Abstract The relationship between Potthoff & Roy's generalized linear model and Rao's conditional model is shown. Rao claimed that his method is more ...

Interpretability has drawn increasing attention in machine learning. Partially linear additive models provide an attractive middle ground between the simplicity of generalized linear model and the ...