Applying Geostatistical Analysis to Crime Data: Car-Related Thefts in the Baltic States.
Applying Geostatistical Analysis to Crime Data: Car-Related Thefts in the Baltic States.
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DOI：
10.1111/j.1538-4632.2010.00782.x
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发表时间：
2010-01
影响因子：
3.6
通讯作者：
Ceccato V
中科院分区：
文献类型：
--
作者：
Kerry R;Goovaerts P;Haining RP;Ceccato V
地统计学方法很少应用于区域层面的犯罪数据。本文使用以前分析过的2000年爱沙尼亚、拉脱维亚和立陶宛与汽车有关的盗窃案件的数据，展示了它们在改善对犯罪模式的解释和理解方面的潜力。变异函数用于告知进攻、社会和经济数据的变化范围。采用面间泊松克里格法和面间克立格法对小数问题引起的噪声进行滤波。后者还被用来制作估计的犯罪风险(每10 000名居民预计犯罪数量)的连续地图，从而减少大空间单位的视觉偏差。在寻求检测最可能的犯罪集群时，通过使用随机模拟的局部集群分析来处理与犯罪风险估计相关的不确定性。因子克立格法被用来估计犯罪风险和解释变量的局部和区域尺度的空间成分。然后使用回归模型确定哪些因素与不同规模的汽车相关盗窃风险相关。
Geostatistical methods have rarely been applied to area-level offense data. This article demonstrates their potential for improving the interpretation and understanding of crime patterns using previously analyzed data about car-related thefts for Estonia, Latvia, and Lithuania in 2000. The variogram is used to inform about the scales of variation in offense, social, and economic data. Area-to-area and area-to-point Poisson kriging are used to filter the noise caused by the small number problem. The latter is also used to produce continuous maps of the estimated crime risk (expected number of crimes per 10,000 habitants), thereby reducing the visual bias of large spatial units. In seeking to detect the most likely crime clusters, the uncertainty attached to crime risk estimates is handled through a local cluster analysis using stochastic simulation. Factorial kriging analysis is used to estimate the local- and regional-scale spatial components of the crime risk and explanatory variables. Then regression modeling is used to determine which factors are associated with the risk of car-related theft at different scales.
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影响因子：
0.8
作者：
Kulldorff, M
通讯作者：
Kulldorff, M
影响因子：
3.6
作者：
ANSELIN, L
通讯作者：
ANSELIN, L
影响因子：
3.6
作者：
Kyriakidis, PC
通讯作者：
Kyriakidis, PC
影响因子：
1.8
作者：
Haining, Robert;Law, Jane;Griffith, Daniel
通讯作者：
Griffith, Daniel
影响因子：
2.9
作者：
Goovaerts, Pierre;Jacquez, Geoffrey M
通讯作者：
Jacquez, Geoffrey M