Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...

Linear mixed model (LMM) methodology is a powerful technology to analyze models containing both the fixed and random effects. The model was first proposed to estimate genetic parameters for unbalanced ...

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 ...

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 ...