Introduction to particle Markov-chain Monte Carlo for disease dynamics modellers - PubMed (original) (raw)

Introduction to particle Markov-chain Monte Carlo for disease dynamics modellers

Akira Endo et al. Epidemics. 2019 Dec.

Free article

Abstract

The particle Markov-chain Monte Carlo (PMCMC) method is a powerful tool to efficiently explore high-dimensional parameter space using time-series data. We illustrate an overall picture of PMCMC with minimal but sufficient theoretical background to support the readers in the field of biomedical/health science to apply PMCMC to their studies. Some working examples of PMCMC applied to infectious disease dynamic models are presented with R code.

Keywords: Hidden Markov process; Particle Markov-chain Monte Carlo; Particle filter; Sequential Monte Carlo; State-space models.

Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

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