EconPapers    
Economics at your fingertips  
 

Bayesian Inference for a Stochastic Epidemic Model with Uncertain Numbers of Susceptibles of Several Types

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

Australian & New Zealand Journal of Statistics, 2003, vol. 45, issue 4, 491-502

Abstract: 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.

Date: 2003
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/1467-842X.00300

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:anzsta:v:45:y:2003:i:4:p:491-502

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=1369-1473

Access Statistics for this article

Australian & New Zealand Journal of Statistics is currently edited by Chris J. Lloyd, Rob J. Hyndman and Russell B. Millar

More articles in Australian & New Zealand Journal of Statistics from Australian Statistical Publishing Association Inc.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-19
Handle: RePEc:bla:anzsta:v:45:y:2003:i:4:p:491-502