Bayesian analysis for mixture of latent variable hidden Markov models with multivariate longitudinal data

• Published in: Computational statistics & data analysis Vol. 132; pp. 190 - 211
• Main Authors: Xia, Ye-Mao, Tang, Nian-Sheng
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.04.2019
• Subjects: Bayesian theory; Finite mixture model; Gibbs sampler; Latent variable hidden Markov model; Markov chain; MCMC; statistical analysis; MCMC; Gibbs sampler; Finite mixture model; Latent variable hidden Markov model

Latent variable hidden Markov models (LVHMMs) are important statistical methods in exploring the possible heterogeneity of data and explaining the pattern of subjects moving from one group to another over time. Classic subject- and/or time-homogeneous assumptions on transition matrices in transition...