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 ...

Various methods have been proposed for smoothing under the monotonicity constraint. We review the literature and implement an approach of monotone smoothing with B-splines for a generalized linear ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Introduction to Generalized Linear Models In this two day course, we provide a comprehensive practical and theoretical introduction to generalized linear models using R. Generalized linear models are ...

Bayesian variable selection has gained much empirical success recently in a variety of applications when the number K of explanatory variables $(x_{1},\ldots ,x_{K})$ is possibly much larger than the ...

Abstract: Phylogenetic Comparative Methods (PCMs) offer a critical approach to analyzing species traits by accounting for evolutionary relationships. Traditionally, these models incorporate ...