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MAD-STEC: a method for multiple automatic detection of space-time emerging clusters

机译:MAD-STEC:一种时空新兴集群的多重自动检测方法

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Crime or disease surveillance commonly rely in space-time clustering methods to identify emerging patterns. The goal is to detect spatial-temporal clusters as soon as possible after its occurrence and to control the rate of false alarms. With this in mind, a spatio-temporal multiple cluster detection method was developed as an extension of a previous proposal based on a spatial version of the Shiryaev-Roberts statistic. Besides the capability of multiple cluster detection, the method have less input parameter than the previous proposal making its use more intuitive to practitioners. To evaluate the new methodology a simulation study is performed in several scenarios and enlighten many advantages of the proposed method. Finally, we present a case study to a crime data-set in Belo Horizonte, Brazil.
机译:犯罪或疾病监视通常依靠时空聚类方法来识别新出现的模式。目的是在出现时空簇后尽快检测并控制误报率。考虑到这一点,开发了一种时空多聚类检测方法,作为基于Shiryaev-Roberts统计量的空间版本的先前建议的扩展。除了具有多聚类检测功能外,该方法的输入参数也比以前的建议要少,这使得从业人员使用起来更加直观。为了评估新方法,在几种情况下进行了仿真研究,并启发了所提出方法的许多优点。最后,我们对巴西贝洛哈里桑塔的犯罪数据集进行了案例研究。

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