统计的
同质性(统计学)
无效假设
统计
空间分析
差异(会计)
自相关
数学
检验统计量
空(SQL)
统计假设检验
计量经济学
空间相关性
同种类的
计算机科学
数据挖掘
组合数学
业务
会计
标识
DOI:10.1080/13658816.2022.2048388
摘要
The concept of local variance is used in the literature on image processing, and, to a lesser extent, in spatial analyses of local heterogeneity. Ord and Getis' local statistic of heterogeneity (LOSH) is used to test the null hypothesis that the local variance is no different from the variance for the entire study area. LOSH is a ratio of two variances, and it is shown here to also be closely related to the Geary statistic, which measures spatial autocorrelation. In this article, the Brown-Forsythe statistic is proposed as a way to test a similar null hypothesis—namely, that the local spatial variance is no different from that observed elsewhere in the study area. Rejection of the null in favor of significant homogeneity can be interpreted as an indicator of local positive spatial autocorrelation. The merits of the proposed test are illustrated via simulations of both null and alternative hypotheses, and the statistic is used to find local areas of homogeneous values in the classic spatial dataset on wheat yields in Rothamsted, England.
科研通智能强力驱动
Strongly Powered by AbleSci AI