Monte Carlo likelihood estimation of mixed-effects state space models with application to HIV dynamics

DOI10.1007/S11424-016-4158-9zbMath1346.93372OpenAlexW2518253223MaRDI QIDQ328844

Aiping Tang, Hai-Lin Feng, Jie Zhou

Publication date: 21 October 2016

Published in: Journal of Systems Science and Complexity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11424-016-4158-9

zbMATH Keywords

state estimationstate space modelmixed-effectsmixture Kalman filter

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Discrete-time control/observation systems (93C55) Estimation and detection in stochastic control theory (93E10)

Related Items (1)

Mixed effects state-space models with Student-t errors

Cites Work

• Following a Moving Target—Monte Carlo Inference for Dynamic Bayesian Models
• Mixed-Effects State-Space Models for Analysis of Longitudinal Dynamic Systems
• Mixture Kalman Filters
• Hierarchical Bayesian Methods for Estimation of Parameters in a Longitudinal HIV Dynamic System
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