The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Analysis of Total Crime Count Data Based on Spatial Association Structure

공간적 연관구조를 고려한 총범죄 자료 분석

  • 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 : 20100100
  • Published : 2010.04.30
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Abstract

Reliability of the estimation is usually damaged in the situation where a linear regression model without spatial dependencies is employed to the spatial data analysis. In this study, we considered the conditional autoregressive model in order to construct spatial association structures and estimate the parameters via the Bayesian approaches. Finally, we compared the performances of the models with spatial effects and the ones without spatial effects. We analyzed the yearly total crime count data measured from each of 25 districts in Seoul, South Korea in 2007.

공간자료분석에서 공간적 상관성을 배제한 일반적인 회귀모형을 통한 모수 추정값들은 신뢰성의 문제가 지적 되어 오고 있다. 본 연구에서는 공간자료의 상관성을 고려한 모형을 구축하기 위하여 일변량 조건부자기회귀모형을 이용하였으며 베이지안 기법을 통하여 모수를 추정하고 공간상관성이 고려된 공간 가산자료모형과 고려되지 않은 일반 가산자료모형을 비교하였다. 연구 대상으로는 서울시의 25개 행정자치구별 총범죄 자료를 이용하였으며 자료분석을 통하여 도시계획과 같은 국가 정책의 수립에 참고자료로 활용될 수 있으리라 판단된다.

Keywords

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