居民日常活动对扒窃警情时空格局的影响
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宋广文, 肖露子, 周素红, 龙冬平, 周淑丽, 刘凯
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Impact of residents' routine activities on the spatial-temporal pattern of theft from person
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Guangwen SONG, Luzi XIAO, Suhong ZHOU, Dongping LONG, Shuli ZHOU, Kai LIU
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表2 不同时段各大场所对扒窃警情影响的空间滞后负二项回归结果 |
Tab. 2 Spatial-lag negative binomial regression results for effects of daily activities on the thefts from person |
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变量类型 | 变量 | 总量模型 | 凌晨 | | 早上 | | 白天 | | 晚上 | 23:00-6:59 | 7:00-9:59 | 10:00-17:59 | 18:00-22:59 | | | b | IRR | b | IRR | | b | IRR | | b | IRR | | b | IRR | | 常数 | 7.744*** | 114.893 | 1.558*** | 4.749 | 2.032*** | 7.629 | 4.379*** | 79.758 | 2.955*** | 19.202 | 社会因素 | 年轻人 | 0.000*** | 1.000 | 0.000*** | 1.000 | 0.000* | 1.000 | 0.000*** | 1.000 | 0.000*** | 1.000 | 外来人口比率 | 0.108 | 1.114 | 0.413* | 1.511 | 0.666*** | | 1.946 | 0.100 | | 1.105 | -0.238 | | 0.788 | 公共交通 | 公交 | 0.001 | 1.001 | 0.000 | 1.000 | 0.003*** | 1.003 | 0.001 | 1.001 | -0.001 | 0.999 | 地铁 | 0.114** | 1.121 | 0.052 | 1.054 | 0.031 | | 1.032 | 0.119** | | 1.126 | 0.129** | | 1.138 | 买菜 | 综合市场 | 0.012 | 1.012 | 0.014* | 1.014 | 0.018** | 1.017 | 0.015 | 1.015 | 0.003 | 1.003 | 购物 | 购物场所 | 0.001** | 1.001 | -0.000 | 1.000 | -0.000 | 1.000 | 0.001*** | 1.001 | 0.001** | 1.001 | 外出吃饭 | 餐馆对数 | 0.027 | 1.027 | 0.283*** | 1.327 | 0.222** | 1.249 | -0.077 | 0.926 | 0.145 | 1.156 | 娱乐 | KTV | 0.019 | 1.019 | 0.020* | 1.020 | 0.009 | 1.009 | 0.018 | 1.019 | 0.023 | 1.023 | 电影院 | 0.094*** | 1.099 | 0.115** | 1.122 | 0.086** | | 1.090 | 0.106*** | | 1.112 | 0.079 | | 1.082 | 酒吧 | 0.031** | 1.032 | 0.029** | 1.030 | 0.009 | | 1.009 | 0.028* | | 1.029 | 0.043*** | | 1.044 | 网吧 | 0.036*** | 1.036 | 0.034*** | 1.034 | 0.030*** | | 1.030 | 0.037*** | | 1.038 | 0.039*** | | 1.040 | 空间滞后变量 | Lag_扒窃 | 0.001*** | 1.001 | 0.003* | 1.003 | 0.002** | 1.002 | 0.001*** | 1.001 | 0.003*** | 1.003 | | α | 0.251*** | 0.178*** | 0.167*** | 0.285*** | | 0.281*** | | | | Moran's I | 0.077*** | 0.092*** | 0.193*** | 0.061*** | | 0.070*** | | |
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