A copula-based Markov chain model for the analysis of binary longitudinal data

DOI10.1080/02664760802499287zbMath1473.62307OpenAlexW2010767963MaRDI QIDQ3184483

Luis Carlos Pérez-Ruíz, Gabriel Escarela, Russell J. Bowater

Publication date: 21 October 2009

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664760802499287

zbMATH Keywords

copulaserial correlationmaximum likelihooddiscrete time seriesprobit regression modelMarkov regression models

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (3)

A linear model-based test for the heterogeneity of conditional correlations ⋮ Unnamed Item ⋮ Multivariate distributions of correlated binary variables generated by pair-copulas

Cites Work

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• Marginalized Transition Models and Likelihood Inference for Longitudinal Categorical Data
• Longitudinal data model selection
• Estimating the dimension of a model
• Statistical Methods in Markov Chains
• Logistic regression for autocorrelated data with application to repeated measures
• Multivariate Dispersion Models Generated From Gaussian Copula

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