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- W2199862011 abstract "Researchers commonly inspect histograms as a first step in data analysis, often finding that these graphs fail to closely align with any of the several hundred ideal frequency distributions. The purpose of this paper is to address how positive spatial autocorrelation-the most frequently encountered in practice-can distort histograms when they are constructed with georeferenced data. Normal, Poisson, and binomial random variables-three widely applicable ones-are studied after establishing appropriate moment generating functions, and are illustrated with selected simulations. The simulations were designed with an ideal surface partitioning, and with the irregular China county surface partitioning. Results show that even moderate levels of positive spatial autocorrelation, while not affecting means, not only inflate variance, but also modify the probabilities of extreme and/or central values, and can alter skewness and kurtosis. A methodology is outlined for recovering the underlying unautocorrelated frequency distributions." @default.
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- W2199862011 date "2011-05-01" @default.
- W2199862011 modified "2023-09-25" @default.
- W2199862011 title "POSITIVE SPATIAL AUTOCORRELATION IMPACTS ON ATTRIBUTE VARIABLE FREQUENCY DISTRIBUTIONS" @default.
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