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Exact Bayesian inference for diffusion-driven Cox processes
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Goncalves, Flavio B., Łatuszyński, Krzysztof G. and Roberts, Gareth O. (2023) Exact Bayesian inference for diffusion-driven Cox processes. Journal of the American Statistical Association . doi:10.1080/01621459.2023.2223791 ISSN 0162-1459. (In Press)
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Official URL: https://doi.org/10.1080/01621459.2023.2223791
Abstract
In this paper, we present a novel methodology to perform Bayesian inference for Cox processes in which the intensity function is driven by a diffusion process. The novelty lies in the fact that no discretization error is involved, despite the non- tractability of both the likelihood function and the transition density of the diffusion. The methodology is based on an MCMC algorithm and its exactness is built on retrospective sampling techniques. The efficiency of the methodology is investigated in some simulated examples and its applicability is illustrated in some real data analyzes.
Item Type: | Journal Article | |||||||||||||||||||||||||||
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Subjects: | Q Science > QA Mathematics Q Science > QC Physics |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | |||||||||||||||||||||||||||
Library of Congress Subject Headings (LCSH): | Poisson processes, Bayesian field theory, Markov processes, Stochastic differential equations, Spatial analysis (Statistics) | |||||||||||||||||||||||||||
Journal or Publication Title: | Journal of the American Statistical Association | |||||||||||||||||||||||||||
Publisher: | American Statistical Association | |||||||||||||||||||||||||||
ISSN: | 0162-1459 | |||||||||||||||||||||||||||
Official Date: | 2023 | |||||||||||||||||||||||||||
Dates: |
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DOI: | 10.1080/01621459.2023.2223791 | |||||||||||||||||||||||||||
Status: | Peer Reviewed | |||||||||||||||||||||||||||
Publication Status: | In Press | |||||||||||||||||||||||||||
Access rights to Published version: | Restricted or Subscription Access | |||||||||||||||||||||||||||
Date of first compliant deposit: | 23 June 2023 | |||||||||||||||||||||||||||
RIOXX Funder/Project Grant: |
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Open Access Version: |
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