Generally speaking, there are two types of outcomes (i.e. response) in statistical analysis: continuous and categorical responses. Linear Models (LM) are one of the most commonly used statistical ...

Generalized linear models (GLMs) are used in high-dimensional machine learning, statistics, communications, and signal processing. In this paper we analyze GLMs when ...

A generalized linear finite mixture model and an EM algorithm to fit the model to data are described. By this approach the finite mixture model is embedded within the general framework of generalized ...

BhGLM is a freely available R package that implements Bayesian hierarchical modeling for high-dimensional clinical and genomic data. It consists of functions for setting up various Bayesian ...

Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...