• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.1
• /
• pp.31-39
• /
• 2017

The goal of this study was to efficiently analyze the relationships of the number of thefts with related factors, considering the spatial patterns of theft crimes. Theft crime data for a 5-year period (2009-2013) were collected from Haeundae Police Station. A logarithmic transformation was performed to ensure an effective statistical analysis and the number of theft crimes was used as the dependent variable. Related factors were selected through a literature review and divided into social, environmental, and defensive factors. Seven factors, were selected as independent variables: the numbers of foreigners, aged persons, single households, companies, entertainment venues, community security centers, and CCTV (Closed-Circuit Television) systems. OLS (Ordinary Least Squares) and GWR (Geographically Weighted Regression) were used to analyze the relationship between the dependent variable and independent variables. In the GWR results, each independent variable had regression coefficients that differed by location over the study area. The GWR model calculated local values for, and could explain the relationships between, variables more efficiently than the OLS model. Additionally, the adjusted R square value of the GWR model was 10% higher than that of the OLS model, and the GWR model produced a AICc (Corrected Akaike Information Criterion) value that was lower by 230, as well as lower Moran's I values. From these results, it was concluded that the GWR model was more robust in explaining the relationship between the number of thefts and the factors related to theft crime.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.3
• /
• pp.725-735
• /
• 2015

The aim of this study is to specifically understand the officetel market by empirical analysis for the determining factors that affect determining the price of the officetel in Busan. In my opinion, it can help officetel providers to select the appropriate size and location that analysis for the factors determining officetel price with market price, and also it can help customers officetel to choice depending on the purpose. So I was conducting this study. In this study, I analyzes the factors determining the price of Officetel using a OLS linear regression, semi-log model, and a robust regression-Busan area Officetel Real Transaction Price as the dependent variable and factors representing the physical characteristics, locational characteristics and regional characteristics as independent variables.

• Health Policy and Management
• /
• v.30 no.1
• /
• pp.26-36
• /
• 2020

Background: The purpose of this study was to analyze the relationship between the regional characteristics and the age-adjusted cardio-cerebrovascular disease mortality rates (SCDMR) in 229 si·gun·gu administrative regions. Methods: SCDMR of man and woman was used as a dependent variable using the statistical data of death cause in 2017. As a representative index of regional characteristics, health behavior factors, socio-demographic and economic factors, physical environment factors, and health care factors were selected as independent variables. Ordinary least square (OLS) regression and geographically weighted regression (GWR) were performed to identify their relationship. Results: OLS analysis showed significant factors affecting the mortality rates of cardio-cerebrovascular disease as follows: high-risk drinking rates, the ratio of elderly living alone, financial independence, and walking practice rates. GWR analysis showed that the regression coefficients were varied by regions and the influence directions of the independent variables on the dependent variable were mixed. GWR showed higher adjusted R² and Akaike information criterion values than those of OLS. Conclusion: If there is a spatial heterogeneity problem as Korea, it is appropriate to use the GWR model to estimate the influence of regional characteristics. Therefore, results using the GWR model suggest that it needs to establish customized health policies and projects for each region considering the socio-economic characteristics of each region.

• Journal of Korean Society of Forest Science
• /
• v.79 no.3
• /
• pp.260-268
• /
• 1990

Two types of ridge regression estimators were compared with the ordinary least squares (OLS) estimator in order to select the "best" estimator when multicollinearitc existed. The ridge estimators were Mallows's (1973) $C_P$-like statistic, and Allen's (1974) PRESS-like statistic. The evaluation was conducted based on the predictive ability of a yield model developed by Matney et al. (1988). A total of 522 plots from the data of the Southwide Loblolly Pine Seed Source study was used in this study. All of ridge estimators were better in predictive ability than the OLS estimator. The ridge estimator obtained by using Mallows's statistic performed the best. Thus, ridge estimators can be recommended as an alternative estimator when multicollinearity exists among independent variables.

• Spatial Information Research
• /
• v.22 no.3
• /
• pp.35-46
• /
• 2014

Population data are usually provided at administrative spatial units in Korea, so areal interpolation is needed for fine-grained analysis. This study aims to compare various methods of areal interpolation for population subgroups rather than the total population. We estimated the number of elderly people and single-person households for small areal units from Dong data by the different interpolation methods using 2010 census data of Seoul, and compared the estimates to actual values. As a result, the performance of areal interpolation methods varied between the total population and subgroup populations as well as between different population subgroups. It turned out that the method using GWR (geographically weighted regression) and building type data outperformed other methods for the total population and households. However, the OLS regression method using building type data performed better for the elderly population, and the OLS regression method based on land use data was the most effective for single-person households. Based on these results, spatial distribution of the single elderly was represented at small areal units, and we believe that this approach can contribute to effective implementation of urban policies.

• Structural Engineering and Mechanics
• /
• v.36 no.2
• /
• pp.225-241
• /
• 2010

In this study, a hybrid search algorithm combining genetic programming with orthogonal least squares (GP/OLS) is utilized to generate prediction models for compressive strength of high performance concrete (HPC) mixes. The GP/OLS models are developed based on a comprehensive database containing 1133 experimental test results obtained from previously published papers. A multiple least squares regression (LSR) analysis is performed to benchmark the GP/OLS models. A subsequent parametric study is carried out to verify the validity of the models. The results indicate that the proposed models are effectively capable of evaluating the compressive strength of HPC mixes. The derived formulas are very simple, straightforward and provide an analysis tool accessible to practicing engineers.

• Health Policy and Management
• /
• v.26 no.1
• /
• pp.30-38
• /
• 2016

Background: This study purposed to analyze the relationship between spatial distribution of Diabetes prevalence rates and regional variables. Methods: The unit of analysis was administrative districts of city gun gu. Dependent variable was the age- and sex- adjusted diabetes prevalence rates and regional variables were selected to represent three aspects: demographic and socioeconomic factor, health and medical factor, and physical environment factor. Along with the traditional ordinary least square (OLS) regression analysis, geographically weighted regression (GWR) was applied for the spatial analysis. Results: Analysis results showed that age- and sex-adjusted diabetes prevalence rates were varied depending on regions. OLS regression showed that diabetes prevalence rates had significant relationships with percent of population over age 65 and financial independence rate. In GWR, the effects of regional variables were not consistent. These results provide information to health policy makers. Conclusion: Regional characteristics should be considered in allocating health resources and developing health related programs for the regional disease management.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.3
• /
• pp.223-235
• /
• 2011

Although ordinary least squares (OLS) regression analysis can be used to examine the spatial relationships between environmental equity and urban quality of life, this global method may mask the local variations in the relationships between them. These geographical variations can not be captured without using local methods. In this context, this paper explores the spatially varying relationships between environmental equity and urban quality of life across the Atlanta metropolitan area by geographically weighted regression (GWR), a local method. Environmental equity and urban quality of life were quantified with an integrated approach of GIS and remote sensing. Results show that generally, there is a negatively significant relationship between them over the Atlanta metropolitan area. The results also suggest that the relationships between environmental equity and urban quality of life vary significantly over space and the GWR (local) model is a significant improvement on the OLS (global) model for the Atlanta metropolitan area.

• The Journal of the Korea Contents Association
• /
• v.15 no.11
• /
• pp.347-358
• /
• 2015

The purpose of this study is to verify if metropolitan area and non-metropolitan area have an influence on health of the elderly and estimate and compare the difference between the two areas. To achieve this purpose, the study was conducted on 4,714 elderly people aged 65 or more among source materials of "The 3rd Korean Longitudinal Study of Ageing in 2010" using OLS regression analysis and Oaxaca's decomposition method. Major results of the study are as follows. First, the elderly living in metropolitan area were found to have better health than the ones in non-metropolitan area(${\beta}=-.044$, p<.01). Second, in the result of looking into 'area' effect alone, which was decomposed to investigate actual effect of the difference between metropolitan area and non-metropolitan area, the elderly living in non-metropolitan area were found to have lower health status than the ones living in metropolitan area, confirming that the health gap among the elderly also originates from the characteristics of residential area(non metropolitan area-metropolitan area: 223.92, 109.50%; metropolitan area-non metropolitan area: -267.18, 130.66%). Through the results of the study, practical and policy implications and future study direction were suggested.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.6
• /
• pp.1457-1469
• /
• 2017

Private education expenses is one of the key issues in Korea and there have been many discussions about it. Academically, most of previous researches for private education expenses have used multiple regression linear model based on ordinary least squares (OLS) method. However, if the data do not satisfy the basic assumptions of the OLS method such as the normality and homoscedasticity, there is a problem with the reliability of estimations of parameters. In this case, quantile regression model is preferred to OLS model since it does not depend on the assumptions of nonnormality and heteroscedasticity for the data. In the present study, the data from a survey on private education expenses, conducted by Statistics Korea in 2015 has been analyzed for investigation of the impacting factors for private education expenses. Since the data do not satisfy the OLS assumptions, quantile regression model has been employed in Bayesian approach by using gibbs sampling method. The analysis results show that the gender of the student, parent's age, and the time and cost of participating after school are not significant. Household income is positively significant in proportion to the same size for all levels (quantiles) of private education expenses. Spending on private education in Seoul is higher than other regions and the regional difference grows as private education expenditure increases. Total time for private education and student's achievement have positive effect on the lower quantiles than the higher quantiles. Education level of father is positively significant for midium-high quantiles only, but education level of mother is for all but low quantiles. Participating after school is positively significant for the lower quantiles but EBS textbook cost is positively significant for the higher quantiles.