A coupled hidden Markov model for disease interactions

To investigate interactions between parasite species in a host, a population of field voles was studied longitudinally, with presence or absence of six different parasites measured repeatedly. Although trapping sessions were regular, a different set of voles was caught at each session, leading to in...

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Veröffentlicht in:	Journal of the Royal Statistical Society Jg. 62; H. 4; S. 609 - 627
Hauptverfasser:	Sherlock, Chris, Xifara, Tatiana, Telfer, Sandra, Begon, Mike
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Blackwell Publishing Ltd 01.08.2013 John Wiley & Sons Ltd Oxford University Press
Schlagworte:	Adaptive Markov chain Monte Carlo sampling Applied statistics Bartonella Covariance Datasets Discrete time Disease Disease models Diseases Economic theory Forward-backward algorithm Gibbs sampler Hidden Markov models Immune response Infections Inference Logistic regression Logistics Longitudinal studies Markov analysis Markov chains Markov models Markovian processes Mathematical models Medical research Monte Carlo simulation Original Parasites Population (statistical) Probability Public health Regression analysis Samples Sampling Statistical analysis Studies Transition probabilities Voles Zoonosis Gibbs sampler Zoonosis Adaptive Markov chain Monte Carlo sampling Hidden Markov models Forward–backward algorithm
ISSN:	0035-9254, 1467-9876
Online-Zugang:	Volltext
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