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Abstract:
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In exploratory analyses of spatial data, typically the primary goal is to asses whether the data exhibit spatial dependence and then, if so, to determine the strength of the spatial dependence. In this talk, we consider a class of statistics called APLEs, which are approximate profile likelihood estimators in common spatial statistical models. Importantly, APLE statistics are constructed to have a closed form. We provide both theoretical and simulation-based evidence to demonstrate that APLEs perform well as both estimators and test. In addition, for the APLE statistic based on SAR model, we propose graphical exploratory tools, which allow us to assess the strength of spatial dependence in the data as a whole and to identify areas of local spatial clustering and outliers. Finally, we use real data to illustrate the use of APLE as an exploratory spatial-data-analysis tool.
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