Nonparametric estimation of the intensity function of a spatial point process on a Riemannian manifold
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Published version
Author(s)
Ward, Scott
Battey, Heather
Cohen, Edward
Type
Journal Article
Abstract
This paper is concerned with nonparametric estimation of the intensity function of a point process on a Riemannian manifold. It provides a first-order asymptotic analysis of the proposed kernel estimator for Poisson processes, supplemented by empirical work to probe the behaviour in finite samples and under other generative regimes. The investigation highlights the scope for finite-sample improvements by allowing the bandwidth to adapt to local curvature.
Date Issued
2023-12-01
Date Acceptance
2023-02-13
Citation
Biometrika, 2023, 110 (4), pp.1009-1021
ISSN
0006-3444
Publisher
Oxford University Press
Start Page
1009
End Page
1021
Journal / Book Title
Biometrika
Volume
110
Issue
4
Copyright Statement
© The Author(s) 2023. Published by Oxford University Press on behalf of Biometrika Trust.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium,
provided the original work is properly cited.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium,
provided the original work is properly cited.
License URL
Identifier
https://academic.oup.com/biomet/advance-article/doi/10.1093/biomet/asad012/7059530
Publication Status
Published
Article Number
asad012
Date Publish Online
2023-02-28