Bayesian methods furnish an attractive approach to inference in generalized linear mixed models. In the absence of subjective prior information for the random-effect variance components, these ...

Conditional Akaike information criterion is derived within the framework of conditional-likelihood-based method for binary response generalized linear mixed models. The criterion essentially is the ...

Project for generalized linear models class at BYU. Modeling the probability that a pitch is a strike using generalized additive models and determining catcher framing abilities and umpire influence ...

The generalized linear mixed models using logit and probit link functions provided similar genetic parameter estimates and predictions of breeding values of the animals when logit/logit and ...

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

Linear Models (LM) are one of the most commonly used statistical methods to analyze continuous outcomes. However, many studies in Engineering, Medical Study, Education, etc. involve categorical ...