盗窃犯罪空间分布与地理因素的关联  

Relationship between spatial distribution of thief crime and geographical factors

作　　者：颜峻[1] 疏学明[1] 袁宏永[1] 

机构地区：[1]清华大学工程物理系,公共安全研究中心,北京100084

出　　处：《清华大学学报（自然科学版）》2010年第2期174-176,186,共4页Journal of Tsinghua University(Science and Technology)

基　　金：国家自然科学基金资助项目(70773069,70833003)

摘　　要：为分析犯罪空间分布成因,将地理加权回归模型用于犯罪空间分布与地理因素关联研究。该模型可以处理空间关系变化过程,求解空间非稳定性问题。以社区盗窃案件发案率为例,建立了盗窃刑事犯罪率与社区人口密度、路网密度、社区距派出所距离等因素之间的局部分析模型,给出了参数估计及显著性检验空间分布图。结果表明,犯罪空间分布与人口、环境等因素的关系随空间位置而改变;地理加权回归模型可以提高参数估计的准确性。The geographical weighted regression （GWR） model is used to analyze the relationships between the spatial distributions of crime and geographical factors to find the cause of crime spatial distributions. The GWR model can capture the spatial variations in the spatially non-stationary problems. The GWR procedure is used to build a local model to analyze the effects of population density, road network density, and distance from police stations on the crime rate at the census traet level to give a set of mappahle parameter estimates and t-values of significance that vary over space. Analytical results demonstrate that the spatial relationship between crime and geographical factors is a spatially non-stationary process and that the GWR model can help improve the accuracy of parameter estimation.

关 键 词：犯罪统计学 普查单位 地理加权回归模型 成因 

分 类 号：D917.9[政治法律—法学]