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PubMed · 16542237

Assessing isotropy for spatial point processes.

Yongtao Guan·Michael Sherman·James A Calvin
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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 L(2) 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 chi(2) 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.

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AnisotropyChi-Square DistributionComputer SimulationDesert ClimateEcologyPlantsStatistics, NonparametricJournal Article

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BibTeXRIS

Yongtao Guan, Michael Sherman, James A Calvin. 2006. Assessing isotropy for spatial point processes.. https://doi.org/10.1111/j.1541-0420.2005.00436.x

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