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Autocorrelation and cross-correlation in time series of homicide and attempted homicide

机译:凶杀案和未遂凶杀案时间序列中的自相关和互相关

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We propose in this paper to establish the relationship between homicides and attempted homicides by a non-stationary time-series analysis. This analysis will be carried out by Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation Analysis (DCCA), and DCCA cross-correlation coefficient, ~(ρDCCA)(n). Through this analysis we can identify a positive cross-correlation between homicides and attempted homicides. At the same time, looked at from the point of view of autocorrelation (DFA), this analysis can be more informative depending on time scale. For short scale (days), we cannot identify autocorrelations, on the scale of weeks DFA presents anti-persistent behavior, and for long time scales (n > 90 days) DFA presents a persistent behavior. Finally, the application of this new type of statistical analysis proved to be efficient and, in this sense, this paper can contribute to a more accurate descriptive statistics of crime.
机译:我们建议通过非平稳时间序列分析来建立凶杀与未遂凶杀之间的关系。该分析将通过去趋势波动分析(DFA),去趋势互相关分析(DCCA)和DCCA互相关系数〜(ρDCCA)(n)进行。通过此分析,我们可以确定凶杀案与未遂凶杀案之间的正相关。同时,从自相关(DFA)的角度来看,根据时间范围,此分析可以提供更多信息。对于小规模(天),我们无法识别自相关,在DFA呈现反持续行为的周数范围内,而在长时间尺度(n> 90天),DFA呈现持续性行为。最后,事实证明,这种新型统计分析的应用是有效的,从这个意义上讲,本文可以为更准确的犯罪描述统计做出贡献。

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