Assessing isotropy for spatial point processes

Yongtao Guan, Michael Sherman, James A. Calvin

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

A common assumption while analyzing spatial point processes is direction invariance, i.e., isotropy. In this article, we propose a formal nonparametric approach to test for isotropy based on the asymptotic joint normality of the sample second-order intensity function. We derive an L2 consistent subsampling estimator for the asymptotic covariance matrix of the sample second-order intensity function and use this to construct a test statistic with a χ2 limiting distribution. We demonstrate the efficacy of the approach through simulation studies and an application to a desert plant data set, where our approach confirms suspected directional effects in the spatial distribution of the desert plant species.

Original languageEnglish (US)
Pages (from-to)119-125
Number of pages7
JournalBiometrics
Volume62
Issue number1
DOIs
StatePublished - Mar 1 2006

Keywords

  • Anisotropy
  • Spatial point process
  • Subsampling

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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