Covariance of empirical functionals for inhomogeneous spatial point processes when the intensity has a parametric form

Jean François Coeurjolly, Yongtao Guan

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper is concerned with the problem of estimating covariances of inhomogeneous second-order reweighted stationary spatial point processes when the intensity of the spatial point process has a parametric form. The proposed estimator is based on kernel techniques. It is a very simple and fast estimator which in addition does not require one to model second and higher moments of the spatial point process. Under very mild assumptions, mainly on characteristics of the point process, we prove the mean squared consistency of our estimator. Finally, we show in a simulation study that the kernel-based covariance estimator outperforms existing methods when it is applied to build confidence intervals of the intensity.

Original languageEnglish (US)
Pages (from-to)79-92
Number of pages14
JournalJournal of Statistical Planning and Inference
Volume155
DOIs
StatePublished - Dec 1 2014

Fingerprint

Spatial Point Process
Estimator
kernel
Point Process
Confidence interval
Simulation Study
Moment
Form
Point process
Kernel

Keywords

  • Covariance estimation
  • Kernel estimation
  • Point processes
  • Spatial statistics

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Statistics and Probability

Cite this

Covariance of empirical functionals for inhomogeneous spatial point processes when the intensity has a parametric form. / Coeurjolly, Jean François; Guan, Yongtao.

In: Journal of Statistical Planning and Inference, Vol. 155, 01.12.2014, p. 79-92.

Research output: Contribution to journalArticle

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