Bayesian Cholesky factor models in random effects covariance matrix for generalized linear mixed models
type: Item
instance of: scholarly article
title: Bayesian Cholesky factor models in random effects covariance matrix for generalized linear mixed models
zbMATH Open document ID: 1506.62103
author: Keunbaik Lee
author: Jae Keun Yoo
published in: Computational Statistics and Data Analysis
publication date: 2018-11-23T00:00:00Z
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 62J12
Mathematics Subject Classification ID: 62F15
Mathematics Subject Classification ID: 62H25
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 6984080
zbMATH Keywords: Cholesky decomposition
zbMATH Keywords: longitudinal data
zbMATH Keywords: heterogeneity
describes a project that uses: BayesDA
MaRDI profile type: Publication
full work available at URL: j.csda.2014.06.016
OpenAlex ID: W2093476011
cites work: Approximate Inference in Generalized Linear Mixed Models
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cites work: Modeling the random effects covariance matrix for generalized linear mixed models
cites work: On modelling mean-covariance structures in longitudinal studies
cites work: Regression models for covariance structures in longitudinal studies
cites work: Joint mean-covariance models with applications to longitudinal data: unconstrained parameterisation
cites work: Maximum likelihood estimation of generalised linear models for multivariate normal covariance matrix
cites work: Dynamic Conditionally Linear Mixed Models for Longitudinal Data
cites work: Bayesian Measures of Model Complexity and Fit
cites work: A moving average Cholesky factor model in covariance modelling for longitudinal data
DOI: 10.1016/J.CSDA.2014.06.016
description: scientific article; zbMATH DE number 6984080