We have developed two scan statistics for detecting clusters of functional data indexed in space. The first method is based on an adaptation of a functional analysis of variance and the second one is based on a distribution-free spatial scan statistic for univariate data. In a simulation study, the distribution-free method always performed better than a nonparametric functional scan statistic, and the adaptation of the anova also performed better for data with a normal or a quasi-normal distribution. Our methods can detect smaller spatial clusters than the nonparametric method. Lastly, we used our scan statistics for functional data to search for spatial clusters of abnormal unemployment rates in France over the period 1998-2013 (divided into quarters).
翻译:我们开发了两种扫描统计数据,用于探测空间指数化功能数据组群,第一种方法基于对差异功能分析的调整,第二种方法基于无分布空间扫描单体数据统计,在模拟研究中,无分配方法的运行总是优于非对称功能扫描统计,新星的改造也优于正常或准正常分布的数据。我们的方法可以探测比非参数方法较小的空间组群。最后,我们利用我们的扫描统计数据搜索1998-2013年期间法国异常失业率的空间组群(分为几个区)。