dissertation · ePrints Soton (University of Southampton) · 2004
Bayesian sampling methods in epidemic and finite mixture models
Currie, Christine Susan Mary
Cited by 0Open access
Abstract
<p>This thesis describes the use of sampling methods in two applications: an epidemic model of tuberculosis (TB) and HIV, and the estimation of the number of components in finite normal mixture models. We use Bayesian statistics for the analysis, which enables us to take into account prior information about parameter values in the case of the epidemic modelling, and smooths the likelihood function when considering finite mixture models. The convergence properties of importance sampling are investigated and methods for diagnosing non-convergence of importance sampling are discussed. We use importance sampling to analyse finite normal mixture models and Marlov Chain Monte Carlo sampling to fit the epidemic model. Results for effectiveness and cost-effectiveness of different interventions against TB and HIV are presented.</p>
Cite this paper
Currie, C. S. M. (2004). Bayesian sampling methods in epidemic and finite mixture models. ePrints Soton (University of Southampton).
Currie, Christine Susan Mary. “Bayesian sampling methods in epidemic and finite mixture models.” ePrints Soton (University of Southampton), 2004.
Currie, Christine Susan Mary. 2004. “Bayesian sampling methods in epidemic and finite mixture models.” ePrints Soton (University of Southampton).
Currie, C.S.M. (2004) ‘Bayesian sampling methods in epidemic and finite mixture models’, ePrints Soton (University of Southampton).
@phdthesis{currie2004bayesian,
title = {{Bayesian sampling methods in epidemic and finite mixture models}},
author = {Currie, Christine Susan Mary},
school = {ePrints Soton (University of Southampton)},
year = {2004}
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