Spreading Disease Modeling Using Markov Random Fields

Stelios Zimeras ()
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Stelios Zimeras: University of the Aegean, Department of Statistics and Actuarial – Financial Mathematics

Chapter Chapter 10 in Quantitative Methods in Demography, 2022, pp 155-163 from Springer

Abstract: Abstract Markov random fields are widely used to model spatial processes. Key components of any statistical analysis using such models are the choice of an appropriate model as the prior distribution and the estimation of prior model parameters. Models for spreading diseases are given based on whether or not the disease succeeds or fails to appear in the region. In this work, the spatial pattern models for spreading diseases have been analyzed considering Markov random fields auto-models. The Gibbs sampler would be used to simulate example images for various parameter combinations.

Keywords: Spreading disease; Markov random fields; Bayesian analysis; Estimation techniques; Auto-logistic; Auto-binomial models (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-3-030-93005-9_10

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DOI: 10.1007/978-3-030-93005-9_10

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