Cubature scheme for spatio-temporal Poisson point processes estimation
N D'Angelo, G Adelfio - arXiv preprint arXiv:2403.10878, 2024 - arxiv.org
arXiv preprint arXiv:2403.10878, 2024•arxiv.org
This work presents the cubature scheme for the fitting of spatio-temporal Poisson point
processes. The methodology is implemented in the R Core Team (2024) package stopp
(D'Angelo and Adelfio, 2023), published on the Comprehensive R Archive Network (CRAN)
and available from https://CRAN. R-project. org/package= stopp. Since the number of
dummy points should be sufficient for an accurate estimate of the likelihood, numerical
experiments are currently under development to give guidelines on this aspect.
processes. The methodology is implemented in the R Core Team (2024) package stopp
(D'Angelo and Adelfio, 2023), published on the Comprehensive R Archive Network (CRAN)
and available from https://CRAN. R-project. org/package= stopp. Since the number of
dummy points should be sufficient for an accurate estimate of the likelihood, numerical
experiments are currently under development to give guidelines on this aspect.
This work presents the cubature scheme for the fitting of spatio-temporal Poisson point processes. The methodology is implemented in the R Core Team (2024) package stopp (D'Angelo and Adelfio, 2023), published on the Comprehensive R Archive Network (CRAN) and available from https://CRAN.R-project.org/package=stopp. Since the number of dummy points should be sufficient for an accurate estimate of the likelihood, numerical experiments are currently under development to give guidelines on this aspect.
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