Advanced SearchSearch Tips
A Comparative Study on Spatial Lattice Data Analysis - A Case Where Outlier Exists -
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Comparative Study on Spatial Lattice Data Analysis - A Case Where Outlier Exists -
Kim, Su-Jung; Choi, Seung-Bae; Kang, Chang-Wan; Cho, Jang-Sik;
  PDF(new window)
Recently, researchers of the various fields where the spatial analysis is needed have more interested in spatial statistics. In case of data with spatial correlation, methodologies accounting for the correlation are required and there have been developments in methods for spatial data analysis. Lattice data among spatial data is analyzed with following three procedures: (1) definition of the spatial neighborhood, (2) definition of spatial weight, and (3) the analysis using spatial models. The present paper shows a spatial statistical analysis method superior to a general statistical method in aspect estimation by using the trimmed mean squared error statistic, when we analysis the spatial lattice data that outliers are included. To show validation and usefulness of contents in this paper, we perform a small simulation study and show an empirical example with a criminal data in BusanJin-Gu, Korea.
Spatial neighborhood;spatial neighborhood weight;spatial autocorrelation;trimed mean squared error;
 Cited by
크리깅을 이용한 아파트 가격 예측,소성현;최승배;강창완;김수정;

Journal of the Korean Data Analysis Society, 2012. vol.14. 1, pp.139-150
김정숙, 황희진, 신기일 (2008). 이웃정보시스템을 이용한 공간 소지역 추정량 비교, <응용통계연구>, 21, 855-866. crossref(new window)

전수영, 임성섭 (2009). 오차항이 SAR(1)을 따르는 공간선형회귀모형에서 일반화 최대엔트로피 추정량에 관한 연구, <한국통계학회논문집>, 16, 265-275. crossref(new window)

황희진, 신기일 (2009). MSPE를 이용한 임금총액 소지역 추정, <응용통계연구>, 22, 403-414. crossref(new window)

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

Cressie, N. and Chan, N. H. (1989). Spatial modeling of regional variables, Journal of the American Statistical Association, 84, 393-401. crossref(new window)

Cressie, N. A. C. (1991). Statistics for Spatial Dat, John Wiley & Sons, New York.

Griffith, D. A. and Layne, L. J. (1999). A Casebook for Spatial Statistical Data Analysis: A Compilation of Analyses of Different Thematic Data Set, Oxford University Press, Oxford.

Jhung, Y. and Swain, P. H. (1996). Bayesian contextual classification based on modified M-estimates and Markov random fields, IEEE Transaction of Pattern Analysis and Machine Interlligence, 34, 67-75.

Moran, P. (1948). The interpretation of statistical maps, Journal of Royal Statistical Society, 10, 243-251.

Smirnov, O. and Anselin, L. (2009). Parallel method of computing the Log-Jacobian of the variable trans-formation for models with spatial interaction on a lattice, Computational Statistics and Data Analysis, 53, 2980-2988. crossref(new window)

Stephen P. K., Silvia C. V., Tamre P. C. and Alice A. S. (1996). S+SpatialStats User's Manual, MathSofh, Inc.: Seattle, Washington.