Bayesian inference for a stochastic epidemic model with uncertain numbers of susceptibles of several types

Yu Hayakawa, Philip D. O'Neill, Darren Upton, Paul S.F. Yip*

*この研究の対応する著者

研究成果: Article査読

7 被引用数 (Scopus)

抄録

A stochastic epidemic model with several kinds of susceptible is used to analyse temporal disease outbreak data from a Bayesian perspective. Prior distributions are used to model uncertainty in the actual numbers of susceptibles initially present. The posterior distribution of the parameters of the model is explored via Markov chain Monte Carlo methods. The methods are illustrated using two datasets, and the results are compared where possible to results obtained by previous analyses.

本文言語English
ページ(範囲)491-502
ページ数12
ジャーナルAustralian and New Zealand Journal of Statistics
45
4
DOI
出版ステータスPublished - 2003 12月
外部発表はい

ASJC Scopus subject areas

  • 統計学および確率
  • 統計学、確率および不確実性

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