Scalable Bayesian Inference for Coupled Hidden Markov and Semi-Markov Models

DOI10.1080/10618600.2019.1654880OpenAlexW2925220679WikidataQ99557789 ScholiaQ99557789MaRDI QIDQ3391423

Bärbel Finkenstädt, Panayiota Touloupou, Simon E. F. Spencer

Publication date: 28 March 2022

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10618600.2019.1654880

zbMATH Keywords

epidemicsMarkov chain Monte Carlo methodsdata augmentationforward-backward algorithmcoupled hidden Markov model

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (3)

Inference for stochastic kinetic models from multiple data sources for joint estimation of infection dynamics from aggregate reports and virological data ⋮ A primer on coupled state-switching models for multiple interacting time series ⋮ Bayesian inference for multistrain epidemics with application to \textit{Escherichia coli} O157:H7 in feedlot cattle

Uses Software

• R
• ggplot2
• foreach
• doParallel

Cites Work

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• Unnamed Item
• Calculating posterior distributions and modal estimates in Markov mixture models
• Adaptive Gibbs samplers and related MCMC methods
• Mixed memory Markov models: Decomposing complex stochastic processes as mixtures of simpler ones
• ggplot2
• Networks of queues and the method of stages
• On Gibbs sampling for state space models
• Bayesian Methods for Hidden Markov Models

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