Spherical Poisson point process intensity function modeling and estimation with measure transport-Reference-Cited by-同舟云学术

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Spherical Poisson point process intensity function modeling and estimation with measure transport

Published:2022-08 Issue: Volume:50 Page:100629
ISSN:2211-6753
Container-title:Spatial Statistics
language:en
Short-container-title:Spatial Statistics

Author:

Ng Tin Lok James,Zammit-Mangion Andrew^ORCID

Funder

Australian Research Council

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Statistics and Probability

Reference44 articles.

1. Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities;Adams,2009

2. inlabru: An R package for Bayesian spatial modelling from ecological survey data;Bachl;Methods Ecol. Evol.,2019

3. Neural Networks for Pattern Recognition;Bishop,1995

4. Neural spatio-temporal point processes;Chen,2020

5. The impact of weather and climate extremes on coral growth;Crabbe,2008

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1. Mixture modeling with normalizing flows for spherical density estimation;Advances in Data Analysis and Classification;2023-10-04

2. Scalable Bayesian Transport Maps for High-Dimensional Non-Gaussian Spatial Fields;Journal of the American Statistical Association;2023-05-02

3. Statistical Deep Learning for Spatial and Spatiotemporal Data;Annual Review of Statistics and Its Application;2023-03-10

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