Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Analysis of Violent Crime Count Data Based on Bivariate Conditional Auto-Regressive Model

이변량 조건부자기회귀모형을이용한강력범죄자료분석

  • Choi, Jung-Soon (Division of Biostatistics and Epidemiology, Medical University of South Carolina) ;
  • Park, Man-Sik (Department of Statistics, Sungshin Women's University) ;
  • Won, Yu-Bok (Department of Information System Planning, Seoul Metropolitan Government) ;
  • Kim, Hag-Yeol (Department of Urban Engineering, Seokyeong University) ;
  • Heo, Tae-Young (Department of Data Information, Korea Maritime University)
  • Received : 20091100
  • Accepted : 20100200
  • Published : 2010.05.31
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Abstract

In this study, we considered bivariate conditional auto-regressive model taking into account spatial association as well as correlation between the two dependent variables, which are the counts of murder and burglary. We conducted likelihood ratio test for checking over-dispersion issues prior to applying spatial poisson models. For the real application, we used the annual counts of violent crimes at 25 districts of Seoul in 2007. The statistical results are visually illustrated by geographical information system.

본 연구에서는 5대 범죄중 사람의 생명과 신체에 심각한 위해를 가하는 강력범죄인 살인과 강도 범죄의 이변량 가산자료에 대해 이변량조건부자기회귀모형을 사용하여 공간상관성을 반영한 강력범죄모형을 제안하였다. 범죄자료와 같은 가산자료에 대한 과대산포 검정을 위해 우도비 검정 실시하였으며, 그 결과 과대산포가 유의하지 않음에 따라 공간포아송모형을 이용하였다. 실증예제로 2007년 서울시에서 제공하는 25개 자치구별 강력범죄자료를 지리정보시스템을 이용하여 강력범죄 발생실태를 시각화하였으며 강력범죄에 영향을 주는 다양한 요인들에 대하여 분석을 실시하였다.

Keywords

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