Stationarity Tests for Spatial Point Processes using Discrepancies

: For testing stationarity of a given spatial point pattern, Guan (2008) proposed a model‐free statistic, based on the deviations between observed and expected counts of points in expanding regions within the sampling window. This article extends his method to a general class of statistics by incorp...

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Bibliographic Details
Published in:Biometrics 2013-06, Vol.69 (2), p.497-507
Main Authors: Chiu, Sung Nok, Liu, Kwong Ip
Format: Article
Language:English
Subjects:
Asymptotic methods
BIOMETRIC METHODOLOGY
biometry
Biometry - methods
Biostatistics
Computer Simulation
data analysis
Discrepancy
equations
Georgia
Longleaf pine data
Models, Statistical
Pinus
Poisson Distribution
simulation models
Spatial point process
Stationarity test
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Summary:: For testing stationarity of a given spatial point pattern, Guan (2008) proposed a model‐free statistic, based on the deviations between observed and expected counts of points in expanding regions within the sampling window. This article extends his method to a general class of statistics by incorporating also such information when points are projected to the axes and by allowing different ways to construct regions in which the deviations are considered. The limiting distributions of the new statistics can be expressed in terms of integrals of a Brownian sheet and hence asymptotic critical values can be approximated. A simulation study shows that the new tests are always more powerful than that of Guan. When applied to the longleaf pine data where Guan's test gave an inconclusive answer, the new tests indicate a clear rejection of the stationarity hypothesis.
ISSN:0006-341X
1541-0420
DOI:10.1111/biom.12031