Bayesian Inference for Spatial Point Processes Via Perfect Sampling
msra(2000)
摘要
We study a Bayesian cluster model for spatial point processes in which observationsare assumed to cluster around a finite collection of underlying landmarks.Perfect sampling from the posterior distribution of landmarks is investigated. Inthe case of Neyman--Scott cluster models, perfect sampling from the posterior isshown to be computationally feasible via a coupling-from-the-past type algorithmof Kendall and Mller. An application to data on leukemia incidence in upstateNew York is...
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关键词
posterior distribution,coupling from the past,bayesian inference
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