A Bootstrap Test Using Maximum Likelihood Ratio Statistics to Check the Similarity of Two 3-Dimensionally Oriented Data Samples

Comparing three-dimensionally oriented datasets is a problem encountered in various branches of earth science. A simple statistical tool for the comparison of two 3-dimensionally oriented datasets using the bootstrap method in line with the usual nonparametric permutation test is described here. This bootstrap test involves the estimation of maximum likelihood ratio statistic for properly constructed joint frequency tables of the datasets to be compared. This test does not use asymptotic result and will work well even for small sample sizes. Also this test does not make any specific distributional assumptions.     

Permutation Methods for Determining the Significance of Spatial Dependence

A class of multivariate nonparametric tests for spatial dependence, Multivariate Sequential Permutation Analyses (MSPA), is developed and applied to the analysis of spatial data. These tests allow the significance level (P value) of the spatial correlation to be computed for each lag class. MSPA is shown to be related to the variogram and other measures of spatial correlation. The interrelationships of these measures of spatial dependence are discussed and the measures are applied to synthetic and real data. The resulting plot of significance level vs. lag spacing, or P-gram, provides insight into the modeling of the semivariogram and the semimADogram. Although the test clearly rejects some models of correlation, the chief value of the test is to quantify the strength of spatial correlation, and to provide evidence that spatial correlation exists     

职业足球比赛期间球场周边扒窃犯罪的空间分布特征研究

现阶段,关于足球比赛等体育活动影响周边区域犯罪风险的研究主要关注于一般性验证,而缺少对比赛期间不同时间范围内犯罪风险的态势分析及相关空间影响因素的研究。本文以英国伯明翰市的维拉公园球场为例开展实证研究,对2005—2009年赛季的104场职业足球比赛在比赛日和对照日、开赛前和开赛后等不同时间范围内球场周边3 km区域内发生的扒窃类案件的空间分布特征进行了分析,并利用负二项回归模型研究了相应案件的空间影响要素。结果表明：维拉公园球场周边区域内比赛日期间的扒窃案件发案量要明显高于对照日,而在具体的时间分布上,比赛日开赛时间前2小时到开赛后1小时内发生的扒窃案件显著偏多,并且案件在比赛日和对照日、比赛日的开赛前和开赛后期间的空间分布特征明显不同;回归分析结果显示,比赛日期间餐饮消费类场所的扒窃案件风险较为突出,且高于对照日,而对照日期间的扒窃案件风险则主要集中于休闲娱乐等常规性犯罪热点场所;在比赛日的开赛前,扒窃案件风险主要分布于一些人群聚集的公共场所,而在开赛后则主要集中于餐饮类场所,且随着比赛的开始扒窃案件的风险有转移的趋势。本研究对开展基于大数据分析的大型体育活动的犯罪风险精准防控具有一定的指导意义。