利用时间序列模型预测侵害人的犯罪行为:以姆万扎地区为例

Lucas Salati, Seleman Majige
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摘要

该研究旨在确定最适合Mwanza针对人的刑事犯罪的最佳统计预测模型。该研究使用了1960年至2018年期间坦桑尼亚警察部队针对人员的刑事犯罪年度时间序列数据。调查结果显示,在姆万扎地区报告的针对人的刑事犯罪平均每年为269起,最高为867起,最低为44起。据报在姆万扎发生的针对人的刑事犯罪呈上升趋势,但每年都不一致。采用RSME、MAPE、AIC和BIC评价模型的预测精度。模型包括ARIMA模型、SMA模型和SES模型。在RSME、MAPE、AIC和BIC的基础上,结果表明,ARIMA(1,1,1)模型最适合Mwanza地区的人身犯罪预测,适用于犯罪预测。所开发的模型是一个有用的工具,可以对未来几年针对个人的刑事犯罪作出合理可靠的预测。这些预测可以提供指导方针,了解刑事犯罪对人是上升还是下降。
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Forecasting Criminal Offenses Against Persons Using Time Series Models: A Case Study of Mwanza Region
The study aimed to determine the best statistical forecasting model that best fit the criminal Offenses against persons in Mwanza. The study used yearly time series data of criminal Offenses against persons from the Tanzania Police Force for the period 1960 to 2018. The findings show that yearly average, the criminal Offenses against persons reported in the Mwanza region was 269, the maximum was 867 and the minimum was 44. The criminal Offenses against persons reported in Mwanza have an upward trend which is inconsistent from year to year. The RSME, MAPE, AIC and BIC were used to assess the forecasting accuracy of the models. The models included the ARIMA model, SMA and SES. On the basis of RSME, MAPE, AIC and BIC the results showed that ARIMA (1, 1, 1) model is the best model that fits the criminal Offenses against persons in the Mwanza region and therefore suitable for forecasting criminal Offenses. The model that has been developed is a useful tool for producing reasonably reliable forecasts of criminal Offenses against persons in future years. These forecasts can provide guidelines in understanding whether the criminal offence against persons rising or falling.
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