Non-parametric adaptive bandwidth selection for kernel estimators of spatial intensity functions

Marie-Colette van Lieshout

doi:10.48550/arXiv.2210.11902

Non-parametric adaptive bandwidth selection for kernel estimators of spatial intensity functions

Marie-Colette van Lieshout

Research output: Working paper › Preprint › Academic

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Abstract

We propose a new fully non-parametric two-step adaptive bandwidth selection method for kernel estimators of spatial point process intensity functions based on the Campbell–Mecke formula and Abramson’s square root law. We present a simulation study to assess its performance relative to the Cronie–Van Lieshout global bandwidth selector and apply the technique to data on induced earthquakes in the Groningen gas field.

Original language	English
Publisher	ArXiv.org
Pages	1-11
Number of pages	11
DOIs	https://doi.org/10.48550/arXiv.2210.11902
Publication status	Published - 21 Oct 2022

Keywords

Adaptive kernel estimation
Bandwidth selection
Campbell–Mecke formula
Induced earthquakes
Intensity function
Point process

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10.48550/arXiv.2210.11902

2022-XArXivLieshout_2210.11902Submitted version, 373 KB

https://arxiv.org/pdf/2210.11902.pdf

1 Article

Non‑parametric adaptive bandwidth selection for kernel estimators of spatial intensity functions
van Lieshout, M.-C., Apr 2024, In: Annals of the Institute of Statistical Mathematics. 76, p. 313–331 19 p.
Research output: Contribution to journal › Article › Academic › peer-review

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Cite this

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KW - Adaptive kernel estimation

KW - Bandwidth selection

KW - Campbell–Mecke formula

KW - Induced earthquakes

KW - Intensity function

KW - Point process

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PB - ArXiv.org

ER -

Non-parametric adaptive bandwidth selection for kernel estimators of spatial intensity functions

Abstract

Keywords

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Research output

Non‑parametric adaptive bandwidth selection for kernel estimators of spatial intensity functions

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