Permutation Methods for Determining the Significance of Spatial Dependence |
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| Authors: | Douglas D Walker Jim C Loftis and Paul W Mielke Jr |
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| Institution: | (1) INTERA KB, Sollentunavägen 63, 191 40 Sollentuna, Sweden;(2) Department of Agricultural and Chemical Engineering, Colorado State University, Fort Collins, Colorado, 80523;(3) Department of Statistics, Colorado State University, Fort Collins, Colorado, 80523 |
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| Abstract: | A class of multivariate nonparametric tests for spatial dependence, Multivariate Sequential Permutation Analyses (MSPA), is developed and applied to the analysis of spatial data. These tests allow the significance level (P value) of the spatial correlation to be computed for each lag class. MSPA is shown to be related to the variogram and other measures of spatial correlation. The interrelationships of these measures of spatial dependence are discussed and the measures are applied to synthetic and real data. The resulting plot of significance level vs. lag spacing, or P-gram, provides insight into the modeling of the semivariogram and the semimADogram. Although the test clearly rejects some models of correlation, the chief value of the test is to quantify the strength of spatial correlation, and to provide evidence that spatial correlation exists |
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| Keywords: | variogram nonparametric significance permutation test |
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