Exact Bayesian inference for diffusion-driven Cox processes
نویسندگان
چکیده
In this paper, we present a novel methodology to perform Bayesian inference for Cox processes in which the intensity function is driven by diffusion process. The novelty lies fact that no discretization error involved, despite non-tractability of both likelihood and transition density diffusion. based on an MCMC algorithm its exactness built retrospective sampling techniques. efficiency investigated some simulated examples applicability illustrated real data analyzes.
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ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2023
ISSN: ['0162-1459', '1537-274X', '2326-6228', '1522-5445']
DOI: https://doi.org/10.1080/01621459.2023.2223791