• Communications for Statistical Applications and Methods
• /
• v.28 no.4
• /
• pp.315-327
• /
• 2021

The Spatial Autoregressive (SAR) models have drawn considerable attention in recent econometrics literature because of their capability to model the spatial spill overs in a feasible way. While considering the Bayesian analysis of these models, one may face the problem of lack of robustness with respect to underlying prior assumptions. The generalized Bayes estimators provide a viable alternative to incorporate prior belief and are more robust with respect to underlying prior assumptions. The present paper considers the SAR model with a set of linear restrictions binding the regression coefficients and derives restricted generalized Bayes estimator for the coefficients vector. The minimaxity of the restricted generalized Bayes estimator has been established. Using a simulation study, it has been demonstrated that the estimator dominates the restricted least squares as well as restricted Stein rule estimators.

• Spatial Information Research
• /
• v.20 no.1
• /
• pp.81-90
• /
• 2012

When analyzing geographical phenomena, two properties need to be considered. One is the spatial dependence structure and the other is a variation or an uncertainty inhibited in a geographic space. Two problems are encountered due to the properties. Firstly, spatial dependence structure, which is conceptualized as spatial autocorrelation, generates heterogeneous geographic landscape in a spatial process. Secondly, generic statistics, although suitable for dealing with stochastic uncertainty, tacitly ignores location information im plicit in spatial data. GIS is a versatile tool for manipulating locational information, while spatial statistics are suitable for investigating spatial uncertainty. Therefore, integrating spatial statistics to GIS is considered as a plausible strategy for appropriately understanding geographic phenomena of interest. Geographic hot-spot analysis is a key tool for identifying abnormal locations in many domains (e.g., criminology, epidemiology, etc.) and is one of the most prominent applications by utilizing the integration strategy. The article aims at reviewing spatial statistical perspective for analyzing spatial processes in the framework of GIS by carrying out empirical analysis. Illustrated is the analysis procedure of using spatial scan statistic for detecting clusters in the framework of GIS. The empirical analysis targets for identifying spatial clusters of breast cancer incidents in Erie and Niagara counties, New York.

• Journal of Korean Elementary Science Education
• /
• v.31 no.4
• /
• pp.490-500
• /
• 2012

This study was to examine elementary male and female students' spatial abilities, science process skills, and graph construction and interpretation abilities in order to understand the effect that their spatial abilities and science process skills would have on their graph abilities. To conduct this study, total 12 classes of 435 pupils, 6 classes each from grades 5 and 6 in elementary schools were selected for subjects. The number of male student was 207 and that of female one was 228 of them. And previous test papers of spatial abilities, of science process abilities, and of graph abilities were retouched and updated for reuse in new tests. The results of this study are briefed as follows: Firstly, when spatial abilities for male and female group were compared, female group showed a little higher rate of correct answering than male, but not providing statistically significant gap. Secondly, the science process skill tests revealed basic process skills of both groups were more excellent than their integrated process skills, while female group was found to have more correct answers than male, all of which were proving statistical distinction. Thirdly, of graphing skills for two groups, the graph interpretation skills turned out to be better than the graph construction skills, with female group scoring higher than male and with meaningful difference. Fourthly, both between spatial abilities and graph abilities, and between science process skills and graph abilities, static correlations existed with statistical meaning. In other words, those with higher spatial abilities or science process skills were to do better in constructing and interpreting graphs.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.24 no.4
• /
• pp.348-356
• /
• 2014

To understand the relationship between road-traffic noise and urban components such as population, building, road-traffic and land-use, the city of Cheongju that already has road-traffic noise maps of daytime and nighttime was selected for this study. The whole area of the city is divided into square cells of a uniform size and for each cell, the urban components are estimated. A spatial representative noise level for each cell is determined by averaging out population-weighted facade noise levels for noise exposure population within the cell during nighttime. The relationship between the representative noise level and the urban components is statistically modeled at the cell level. Specially, we introduce a spatial auto regressive model and a spatial error model that turns out to explain above 85 % of the noise level. These findings and modeling methods can be used as a preliminary tool for environmental planning and urban design in modern cities in consideration of noise exposure.

• The Korean Journal of Applied Statistics
• /
• v.19 no.1
• /
• pp.57-67
• /
• 2006

In sampling survey, nonresponse tend to occur inevitably. If we use information from respondents only, the estimates will be baised. To overcome this, various non-response imputation methods have been studied. If there are few auxiliary variables for replacing missing imputation or spatial autocorrelation exists between respondents and nonrespondents, spatial autocorrelation can be used for missing imputation. In this paper, we apply several nonresponse imputation methods including spatial imputation for the analysis of farm household economy data of the Gangwon-Do in 2002 as an example. We show that spatial imputation is more efficient than other methods through the numerical simulations.

• The Mathematical Education
• /
• v.41 no.1
• /
• pp.45-58
• /
• 2002

This study was conducted to investigate the gender-related effects of two instructional programs on spatial visualization skills of ninth grade students. Two instructional programs were developed for this study: a web-based virtual reality program and a paper-based program. 194 ninth graders from two middle schools in Seoul participated in this study. Six classes were divided into experimental groups and control groups. The Middle Grades Mathematics Projects (MGMP) Spatial Visualization Test was used to measure spatial visualization skills. The data analysis indicated that both the web-based and paper-based programs were effective to improve spatial visualization skills to treatment groups. Although boys'test mean scores were higher than girls' in the pretest, when deleting the effect of covariance of pretest, there were no statistical significance in the post-test. Girls in the treatment groups favored the paper-based spatial visualization program. These results imply that spatial training may benefit girls' performance more than that of boys and mode of instructional programs can create gender-related differences regarding spatial visualization skills.

• Journal of Korean Association for Spatial Structures
• /
• v.19 no.4
• /
• pp.14-18
• /
• 2019

• Journal of Power System Engineering
• /
• v.4 no.2
• /
• pp.40-45
• /
• 2000

Some engineering materials are often known to have considerable spatial variation in their resisting strength and other properties. The objective of this study is to investigate the averaging effect and the applicability of extremal statistic for the statistical size effect. In the present study, it is assumed that the material property is a stationary random process in space. The theoretical autocorrelation function of the material strength are discussed for several correlation lengths. And, in order to investigate the statistical size effect, the material properties was simulated by using the non-Gaussian random process method. The material properties were plotted on the Weibull probability papers. The main results are summarized as follows: The autocorrelation function of the material properties are almost independent of the averaging length. The variance decreases with increasing the averaging length. As correlation length is smaller, the slope is larger. And also, it was found that Weibull statistics based on the weakest-link model could not explain the spatial variation of material properties with respect to the size effect satisfactory.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.388-393
• /
• 2002

Remote sensing data is collected and analyzed to enhance understanding of the terrestrial surface. Since Landsat satellite was launched in 1972, many researches using multispectral data has been achieved. Recently, with the availability of airborne and satellite hyperspectral data, the study on hyperspectral data are being increased. It is known that as the number of spectral bands of high-spectral resolution data increases, the ability to detect more detailed cases should also increase, and the classification accuracy should increase as well. In this paper, we classified the hyperspectral and multispectral data and tested the classification accuracy. The MASTER(MODIS/ASTER Airborne Simulator, 50channels, 0.4~13$\mu$m) and Landsat TM(7channels) imagery including Yeong-Gwang area were used and we adjusted the classification items in several cases and tested their classification accuracy through statistical comparison. As a result of this study, it is shown that hyperspectral data offer more information than multispectral data.

• The Korean Journal of Applied Statistics
• /
• v.18 no.2
• /
• pp.271-280
• /
• 2005

Kriging methods as traditional spatial data analysis methods and geographical weighted regression models as statistical analysis methods are compared. In this paper, we apply data from the Ministry of Environment to spatial analysis for practical study. We compare these methods to performance with monthly carbon monoxide observations taken at 116 measuring area of air pollution in 1999.