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S-maup: Statistical test to measure the sensitivity to the modifiable areal unit problem

机译:S-maup:统计测试用于测量对可修改面积单位问题的敏感性

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摘要

This work presents a nonparametric statistical test, S-maup, to measure the sensitivity of a spatially intensive variable to the effects of the Modifiable Areal Unit Problem (MAUP). To the best of our knowledge, S-maup is the first statistic of its type and focuses on determining how much the distribution of the variable, at its highest level of spatial disaggregation, will change when it is spatially aggregated. Through a computational experiment, we obtain the basis for the design of the statistical test under the null hypothesis of non-sensitivity to MAUP. We performed an exhaustive simulation study for approaching the empirical distribution of the statistical test, obtaining its critical values, and computing its power and size. The results indicate that, in general, both the statistical size and power improve with increasing sample size. Finally, for illustrative purposes, an empirical application is made using the Mincer equation in South Africa, where starting from 206 municipalities, the S-maup statistic is used to find the maximum level of spatial aggregation that avoids the negative consequences of the MAUP.
机译:这项工作提出了一种非参数统计检验S-maup,用于测量空间密集型变量对可修改的地域单位问题(MAUP)的敏感性。据我们所知,S-maup是该类型的第一个统计数据,重点在于确定变量的分布在其空间最高分解级别时在空间上聚合时将发生多少变化。通过计算实验,我们获得了对MAUP不敏感的零假设下统计测试设计的基础。我们进行了详尽的模拟研究,以接近统计检验的经验分布,获得其临界值并计算其功效和规模。结果表明,总体而言,统计量和功效随样本量的增加而提高。最后,出于说明目的,使用南非的Mincer方程进行了经验应用,从206个城市开始,使用S-maup统计量来查找避免MAUP带来负面影响的最大空间聚集水平。

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