Perfect Sampling for Gibbs Point Processes Using Partial Rejection Sampling
classification
🧮 math.PR
keywords
processessamplinginteractionperfectalgorithmgibbspartialpoint
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We present a perfect sampling algorithm for Gibbs point processes, based on the partial rejection sampling of Guo et al. (2017). Our particular focus is on pairwise interaction processes, penetrable spheres mixture models and area-interaction processes, with a finite interaction range. For an interaction range $2r$ of the target process, the proposed algorithm can generate a perfect sample with $O(\log(1/r))$ expected running time complexity, provided that the intensity of the points is not too high.
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