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An Approximation for the Rank Adjacency Statistic for Spatial Clustering with Sparse Data

机译:具有稀疏数据的空间聚类的秩邻接统计量的逼近

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摘要

The rank adjacency statistic D provides a simple method to assess regional clustering. It is defined as the weighted average absolute difference in ranks of the data, taken over all possible pairs of adjacent regions. In this paper the usual normal approximation to the D statistic is found to give inaccurate results if the data are sparse and some regions have tied ranks. Adjusted formulae for the moments of D that allow for the existence of ties are derived. An example of analyses of sparse mortality data (with many regions having no deaths, and hence tied ranks) showed satisfactory agreement between the adjusted formulae and the empirical distribution of the D statistic. We conclude that the D statistic, when used with adjusted moments, provides a valid approximate method to evaluate spatial clustering, even in sparse data situations.
机译:等级邻接统计D提供了一种评估区域聚类的简单方法。它定义为在所有可能的相邻区域对上获得的数据等级的加权平均绝对差。在本文中,如果数据稀疏且某些区域的等级并列,则通常对D统计量的正态近似值得出的结果不准确。推导了D时刻允许平杆存在的调整公式。稀疏死亡率数据分析的一个例子(许多地区没有死亡,因此排名并列)表明,调整后的公式与D统计量的经验分布之间具有令人满意的一致性。我们得出的结论是,D统计量与调整后的矩一起使用时,即使在数据稀疏的情况下,也提供了一种有效的近似方法来评估空间聚类。

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