Perfect simulation and inference for point processes given noisy observations
UNSPECIFIED. (2004) Perfect simulation and inference for point processes given noisy observations. COMPUTATIONAL STATISTICS, 19 (2). pp. 317-336. ISSN 0943-4062Full text not available from this repository.
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|
|Subjects:||Q Science > QA Mathematics|
|Journal or Publication Title:||COMPUTATIONAL STATISTICS|
|Publisher:||PHYSICA-VERLAG GMBH & CO|
|Number of Pages:||20|
|Page Range:||pp. 317-336|
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