• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.835-844
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• 2003

A difficulty in spatial data analysis is to choose a suitable theoretical variogram. Generally mean squares error(MSE) is used as a criterion of selection. However researchers encounter the case that the values of MSE are almost the same whereas the estimates of parameters are different. In this case, the selection criterion based on MSE should take into account the parameter estimates. In this paper we study on the method of selecting a variogram using spatial correlation.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.253-262
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• 2008

The main objective of this paper is to formulate a generalized procedure to extract the first four moments of univariate spatial association measures for statistical testing under the normality assumption and to evaluate the viability of hypothesis testing based on the normal approximation for each of the spatial association measures. The main results are as follows. First, predicated on the previous works, a generalized procedure under the normality assumption was derived for both global and local measures. When necessary matrices are appropriately defined for each of the measures, the generalized procedure effectively yields not only expectation and variance but skewness and kurtosis. Second, the normal approximation based on the first two moments for the global measures fumed out to be acceptable, while the notion did not appear to hold to the same extent for their local counterparts mainly due to the large magnitude of skewness and kurtosis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.391-397
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• 2008

This paper analyzes the spatial patterns of population distribution in Seoul Metropolitan Area in terms of spatial association using spatial statistics and spatial exploratory technique. Our empirical analysis based on global index shows that, in Seoul Metropolitan Area, the population had been distributed with strong positive spatial association over the period of 1980-2005. It implies that the population of each region is affected by the population distribution of adjacent regions. In addition, the analysis using local index was conducted for detecting the local patterns of spatial association, and the result shows that the clusters of population had been moved in the direction of West(Incheon and Bucheon) and South(Anyang and Seongnam) of Seoul where a large scale of lands or towns were developed over the period. These results will be the preliminary data for establishing management and development plans of Seoul Metropolitan Area.