Comparison of spatial variables over subregions using a block bootstrap
In environmental and agricultural studies, it is often of interestto compare spatial variables across different regions. Traditional statistical tools that assume independent samples are inadequate because of potential spatial correlations. In this article, spatial dependence is accounted for by a random field model, and a non parametric test is developed to compare the overall distributions of variables in two neighboring regions. Sampling distribution of the test statistic is estimated by a spatial block bootstrap. For illustration, the procedure is applied to study root-lesion nematode populations on a production farm in Wisconsin. Choices of the bootstrap block size are investigated via a simulation study and results of the test are compared to traditional approaches.
Key WordsEmpirical distribution function Random field Spatial block bootstrap Two-sample test
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