Orthogonal series estimation of the pair correlation function of a spatial point process

Abdollah Jalilian, Yongtao Guan, Rasmus Waagepetersen

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

The pair correlation function is a fundamental spatial point process characteristic that, given the intensity function, determines second order moments of the point process. Non-parametric estimation of the pair correlation function is a typical initial step of a statistical analysis of a spatial point pattern. Kernel estimators are popular but especially for clustered point patterns suffer from bias for small spatial lags. In this paper we introduce an orthogonal series non-parametric estimator. It is consistent and asymptotically normal according to our theoretical and simulation results. In our simulations the new estimator outperforms the kernel estimators, in particular for Poisson and clustered point processes.

Original languageEnglish (US)
Pages (from-to)769-787
Number of pages19
JournalStatistica Sinica
Volume29
Issue number2
DOIs
StatePublished - Jan 1 2019

Keywords

  • Asymptotic normality
  • Consistency
  • Kernel estimator
  • Orthogonal series estimator
  • Pair correlation function
  • Spatial point process

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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