5 papers
Gradient Boosted Mixed Models: Flexible Estimation of Mean and Variance Components for Clustered Data
Mitchell L. Prevett, Francis K. C. Hui, Zhi Yang Tho +2
We introduce a novel way to combine gradient boosting with mixed effects models, whereby the mean and variance components are learned jointly as functions of covariates via likelih…
A Single Index Approach to Integrated Species Distribution Modeling for Fisheries Abundance Data
Quan Vu, Francis K. C. Hui, A. H. Welsh +3
In fisheries ecology, species abundance data are often collected by multiple surveys, each with unique characteristics. This article is motivated by a dataset of Atlantic sea scall…
Joint Mean and Correlation Regression Models for Multivariate Data
Zhi Yang Tho, Francis K. C. Hui, Tao Zou
We propose a joint mean and correlation regression model for multivariate discrete and (semi-)continuous response data, that simultaneously regresses the mean of each response agai…
An Ising Similarity Regression Model for Modeling Multivariate Binary Data
Zhi Yang Tho, Francis K. C. Hui, Tao Zou
Understanding the dependence structure between response variables is an important component in the analysis of correlated multivariate data. This article focuses on modeling depend…
Random Effects Misspecification and its Consequences for Prediction in Generalized Linear Mixed Models
Quan Vu, Francis K. C. Hui, Samuel Muller +1
When fitting generalized linear mixed models (GLMMs), one important decision to make relates to the choice of the random effects distribution. As the random effects are unobserved,…