安徽省火灾经济损失的尾部分布研究  

The tail distribution of fire loss data in Anhui province

作　　者：陈震[1,2] 陆松[2] 李国辉[2] 张和平[2] 

机构地区：[1]合肥市公安消防支队,合肥230000 [2]中国科学技术大学火灾科学国家重点实验室,合肥230026

出　　处：《火灾科学》2013年第3期161-166,共6页Fire Safety Science

基　　金：国家自然科学基金项目资助(91024027)

摘　　要：采用极大似然估计对安徽火灾经济损失进行了幂律分布拟合,采用Kolmogorov-Smirnov统计判断拟合优度,并选择了4种供选分布作为对比,研究何种分布更适用于描述火灾经济损失数据。研究发现,当经济损失大于100万元时,数据明显偏离幂律分布,通过p值可以拒绝数据服从幂律分布的假设。在5种分布中指数截断幂律分布的拟合效果最好,通过指数截断能够描述数据末端偏离幂律行为的现象。放火和生产作业两类原因的火灾,不仅满足幂律分布,而且指数截断幂律分布的拟合效果最优;不明确原因和静电两类原因的火灾,经济损失仅满足幂律分布;其他7种火灾原因对应的损失数据不能通过幂律分布拟合的p值检验。The power-law distribution of fire loss statistics in Anhui province was estimated by means of Maximum likelihood estimators.The goodness-of-fit test of power-law estimation was conducted in terms of Kolmogorov-Smirnov statistics.In order to judge whether it is possible another distribution might give a good or better fit,four alternative distributions were chosen and analyzed.According to results,the data significantly diverges from power-law distribution when the loss is over thousand Yuan.As the p-value of goodness-of-fit is zero,the power-law distribution is not a plausible hypothesis for the data.The power-law with an exponential cutoff is clearly favored over the other four distributions,and it can depict the deviation from power-law distribution in the end of loss.For fires caused by arson and working,their loss data pass the p-value of goodness-of-fit test,and the power-law with an exponential cutoff is more favored than the power-law distributions.For fires caused by unknown and electrostatic,their loss data pass the p-value of goodness-of-fit test as well,and power-law is the best fitting.For fires caused by the other 7causes,their loss data cannot pass the p-value of goodness-of-fit test.

关 键 词：火灾 经济损失 幂律分布 统计分析 

分 类 号：X932[环境科学与工程—安全科学] O213[理学—概率论与数理统计]