The Application of Kernel Estimation in Analysis of Crime Hot Spots

Yan-yan Wang (), Zhi-hong Sun, Lu Pan, Ting Wang and Da-hu Zhang
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Yan-yan Wang: Air Force Service College
Zhi-hong Sun: Air Force Service College
Lu Pan: Air Force Service College
Ting Wang: Air Force Service College
Da-hu Zhang: Air Force Service College

Chapter Chapter 146 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 1379-1385 from Springer

Abstract: Abstract In order to analyze crime hot spots, we use Kernel estimation. The choice of Kernel function and Band-width is critical in kernel density estimation, which decides the accuracy of the estimation. We choose Gauss kernel and further obtain the optimal Band-width in the sense of square error MISE. Using Kernel estimation, not only can we calculate the density of crime in the region, but also accurately show the areas with the relative high-crime density and get the maximum point according to the information about the previous criminal spots. Last we use Kernel estimation to predict Peter Sutcliffe “the Yorkshire Ripper” 11th criminal location based on the previous criminal locations in the Serial murders. Finally we can get the range of the criminal hot zone: Longitude: 53.6875–53.8125 N; Altitude: 1.775–1.815 W. In fact, the coordinate of Peter’s 11th criminal location is (53.817 N, 1.784 W). From this, it can be seen that our estimation is relatively accurate.

Keywords: Band-width; Crime hot spots; Kernel estimation; Kernel function; MISE (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-38391-5_146

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DOI: 10.1007/978-3-642-38391-5_146

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