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Analysis of Total Crime Count Data Based on Spatial Association Structure
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 Title & Authors
Analysis of Total Crime Count Data Based on Spatial Association Structure
Choi, Jung-Soon; Park, Man-Sik; Won, Yu-Bok; Kim, Hag-Yeol; Heo, Tae-Young;
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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.
Crime counts;spatial association;conditional autoregressive model;generalized Poisson distribution;negative binomial distribution;
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우리나라 산불 발생의 지역별 공간자기상관성에 관한 연구,김문일;곽한빈;이우균;원명수;구교상;

한국지형공간정보학회지, 2011. vol.19. 2, pp.29-37
A Study on Risk Evaluation of Crime in the Seoul Metropolitan Area based on Poisson Regression Model,;;;;

응용통계연구, 2012. vol.25. 5, pp.865-875 crossref(new window)
공간모형을 이용한 수질오염물질의 공간적 예측 및 평가에 대한 연구,강태구;이혁;강일석;허태영;

한국물환경학회지, 2014. vol.30. 4, pp.409-417 crossref(new window)
공간자료의 기하학적 비등방성 연구,고혜지;박만식;

응용통계연구, 2014. vol.27. 5, pp.755-771 crossref(new window)
일반화된 포아송모형을 이용한 교통사고 자료 분석 및 상대위험도 추정,강일석;허태영;

Journal of the Korean Data Analysis Society, 2015. vol.17. 4B, pp.1933-1944
A Study on Spatial Prediction of Water Quality Constituents Using Spatial Model, Journal of Korean Society on Water Environment, 2014, 30, 4, 409  crossref(new windwow)
A Study on Risk Evaluation of Crime in the Seoul Metropolitan Area based on Poisson Regression Model, Korean Journal of Applied Statistics, 2012, 25, 5, 865  crossref(new windwow)
On the Geometric Anisotropy Inherent In Spatial Data, Korean Journal of Applied Statistics, 2014, 27, 5, 755  crossref(new windwow)
윤성도 (2004). 이산종속변인의 분석을 위한 공간계량경제모형: 베이지안 접근방법과 깁스 표본추출 방법을 응용하여, 대학원생우수논문집. 통계개발원.

이성우 (2004). <서울시 범죄발생의 도시계회적 함의>, 서울시정개발연구원.

이성우, 조중구 (2006). 공간적, 환경적 요인이 범죄 피해에 미치는 영향, <서울도시 연구>, 7, 57-76.

Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle, In B. Petrox and F. Caski (Eds.), Second International Symposium on Information Theory, 267-281.

Besag, J. (1974). Spatial interaction and the statistical analysis of lattice systems(with discussions), Journal of the Royal Statistical Society, Series B, 36, 192-236.

Carlin, B. P. and Banerjee, S. (2003). Hierarchical multivariate CAR models for spatio-temporally correlated survival data (with discussion). In Bayesian Statistics 7, eds. J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith and M. West. Oxford Univeristy Press, Oxford.

Consul, P. (1989). Generalized Poisson Distributions. Properties and Applications, Marcel Dekker, Inc., New York.

Consul, P. and Jain, G. (1973). A generalization of the poisson distributions, Technometrics, 15, 791-799. crossref(new window)

Griffith, D. (1996). Spatial autocorrelation and eigenfunctions of the geographic weights matrix accompanying georeferenced data, The Canadian Geographer, 40, 351-367. crossref(new window)

Heo, T. Y. and Hughes-Oliver, J. (2009). Uncertainty adjustments to determine atmospheric dispersion models, International Journal of Environmental Pollution, In press.

Jin, X., Carlin, B. P. and Banerjee, S. (2005). Generalized hierarchical multivariate CAR models for areal data, Biometrics, 61, 950-961. crossref(new window)

Johnson, N. L., Kotz, S. and Kemp, A. W. (1993). Univariate Discrete Distributions. 2nd ed., Wiley, New York.

Sain, S. R. and Cressie, N. (2002). Multivariate lattice models for spatial environmental data, In ASA Proceedings of the Joint Statistical Meetings, 2820-2825, American Statistical Association, Alexandria, VA.

Schwarz, G. (1978). Estimating the dimension of a model, Annals of Statistics, 6, 461-464. crossref(new window)

Spiegelhalter, D. J., Best, N. G., Carlin, B. P. and Van der Linde, A. (2002). Bayesian measures of model complexity and fit, Journal of the Royal Statistical Society, Series B, 64, 583-639. crossref(new window)