Abstract
Monte Carlo methods have a long history in spatial statistics, and have often been used very effectively to sidestep problems of analytical or computational intractability. On the other hand, bootstrap and other non-parametric methods have made no impact and are rarely considered. The reasons are immediate but often overlooked. The author was once asked to referee a paper on the spatial organization of monkey troops, in which the positions were recorded every ten minutes. After a page or so on the virtues of “distribution-free tests”, these were used to test hypotheses about the dominant male being the centre of the troop’s movements. Unfortunately for this study, “distribution-free” tests do make one assumption, independence, there violated in both space and time. More generally, resampling methods depend on at least exchangeability.
Work done whilst at the Department of Statistics, University of Strathclyde, Glasgow.
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Ripley, B.D. (1992). Applications of Monte Carlo Methods in Spatial and Image Analysis. In: Jöckel, KH., Rothe, G., Sendler, W. (eds) Bootstrapping and Related Techniques. Lecture Notes in Economics and Mathematical Systems, vol 376. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-48850-4_6
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DOI: https://doi.org/10.1007/978-3-642-48850-4_6
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