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Perfect simulation and inference for point processes given noisy observations
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UNSPECIFIED (2004) Perfect simulation and inference for point processes given noisy observations. COMPUTATIONAL STATISTICS, 19 (2). pp. 317-336. ISSN 0943-4062.
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Abstract
The paper is concerned with the exact simulation of an unobserved true point process conditional on a noisy observation. We use dominated coupling from the past (CFTP) on an augmented state space to produce perfect samples of the target marked point process. An optimized coupling of the target chains makes the algorithm considerable faster than with the standard coupling used in dominated CFTP for point processes. The perfect simulations are used for inference and the results are compared to an ordinary Metropolis-Hastings sampler.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics | ||||
Journal or Publication Title: | COMPUTATIONAL STATISTICS | ||||
Publisher: | PHYSICA-VERLAG GMBH & CO | ||||
ISSN: | 0943-4062 | ||||
Official Date: | 2004 | ||||
Dates: |
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Volume: | 19 | ||||
Number: | 2 | ||||
Number of Pages: | 20 | ||||
Page Range: | pp. 317-336 | ||||
Publication Status: | Published |
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