Orthogonal series estimation of the paircorrelation function of a spatial point process

Abdollah Jalilian, Yongtao Guan, Rasmus Waagepetersen

Research output: Contribution to journalJournal articleResearchpeer-review

7 Citations (Scopus)

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
JournalStatistica Sinica
Volume29
Pages (from-to)769-787
ISSN1017-0405
DOIs
Publication statusPublished - 2019

Keywords

  • Asymptotic normality
  • consistency
  • kernel estimator
  • orthogonal series estimator
  • pair correlation function
  • spatial point process

Fingerprint

Dive into the research topics of 'Orthogonal series estimation of the paircorrelation function of a spatial point process'. Together they form a unique fingerprint.

Cite this