Perfect simulation of point patterns from noisy observations
نویسندگان
چکیده
The paper is concerned with the Bayesian analysis of point processes which are observed with noise. It is shown how to produce exact samples from the posterior distribution of the unobserved true point pattern given a noisy observation. The algorithm is a perfect simulation method which applies dominated Coupling From The Past (CFTP) to a spatial birth-and-death process. Dominated CFTP is made amenable by simulating on an augmented state space. We discuss how to use this perfect simulation algorithm in a statistical inference problem of pratical importance and describe the merits and the limitations of the method.
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