학술논문
APPROXIMATE BAYESIAN INFERENCE OF A STOCHASTIC DISCRETE COMPARTMENTAL MODEL MOTIVATED BY COVID-19 PANDEMIC.
Document Type
Article
Author
Source
Subject
*BAYESIAN field theory
*COVID-19 pandemic
*MOTIVATION (Psychology)
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Language
ISSN
2519-4445
Abstract
In this paper we construct a stochastic discrete compartmental model from a set of hypotheses about the spread and evolution of an epidemic at the individual level. This model is motivated by the specificities of COVID-19 pandemic. Given the complexity of the likelihood of the model, an approximate Bayesian inference algorithm is proposed to estimate model parameters. Simulated datasets are used to test the efficiency of the proposed algorithm. We illustrate the introduced model on Morocco COVID-19 data. [ABSTRACT FROM AUTHOR]