title: MCMC methods for putative pollution source problems in environmental epidemiology.
abstract: This paper demonstrates the use of the Gibbs Sampler and other Markov Chain Monte Carlo (MCMC) methods in two applications in environmental epidemiology. The first example concerns the application of a Metropolis-Hastings/Gibbs sampler to a Cox process with a direction-dependent cluster variance parameter. The second example consists of the estimation of the posterior (spatial) distribution of a putative location.
authors.affiliation: Department of Mathematical & Computer Sciences, University of Abertay Dundee, U.K.
authors.forename: A B
authors.initials: AB
authors.lastname: Lawson
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D004787:Environmental Pollution / Q000706:statistics & numerical data*; D006801:Humans; D007220:Industrial Waste / Q000009:adverse effects; D007822:Laryngeal Neoplasms / Q000453:epidemiology / Q000209:etiology; D016013:Likelihood Functions; D008390:Markov Chains; D015233:Models, Statistical; D009010:Monte Carlo Method
chemical_list: D007220:Industrial Waste