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Comparing the Performances of Diggle's Tests of Spatial Randomness for Small Samples with and without Edge‐Effect Correction: Application to Ecological Data
Author(s) -
Gignoux Jacques,
Duby Camille,
Barot Sébastian
Publication year - 1999
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.1999.00156.x
Subject(s) - randomness , statistics , enhanced data rates for gsm evolution , mathematics , null hypothesis
Summary. Diggle's tests of spatial randomness based on empirical distributions of interpoint distances can be performed with and without edge‐effect correction. We present here numerical results illustrating that tests without the edge‐effect correction proposed by Diggle (1979, Biometrics 35 , 87–101) have a higher power for small sample sizes than those with correction. Ignoring the correction enables detection of departure from spatial randomness with smaller samples (down to 10 points vs. 30 points for the tests with correction). These results are confirmed by an example with ecological data consisting of maps of two species of trees in a West African savanna. Tree numbers per species per map were often less than 20. For one of the species, for which maps strongly suggest an aggregated pattern, tests without edge‐effect correction enabled rejection of the null hypothesis on three plots out of five vs. on only one for the tests with correction.