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Clustering vs. relative location: Measuring spatial interaction between retail outlets

机译:聚类与相对位置:衡量零售店之间的空间互动

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摘要

This paper presents a new multivariate spatial statistic developed to identify different interaction patterns between competing retail outlets. In order to define when two outlets are located relatively close to each other, a topological proximity criterion is suggested. Asymptotic properties of the new statistic are derived analytically and finite sample properties are obtained through Monte Carlo simulations. Various simulation experiments confirm that the statistic is robust and that it can distinguish pairwise categorical association from clustering in the joint population. To demonstrate its usefulness, the statistic is applied to competing retail chains in two retail sectors.
机译:本文提出了一种新的多元空间统计数据,以识别竞争性零售网点之间的不同交互方式。为了定义两个出口何时彼此相对靠近,建议使用拓扑接近性准则。通过分析得出新统计量的渐近性质,并通过蒙特卡洛模拟获得有限样本性质。各种模拟实验证实了该统计数据的鲁棒性,并且可以区分成对分类关联与联合种群中的聚类。为了证明其有用性,该统计数据应用于两个零售部门中竞争激烈的零售链。

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