• 보건행정학회지
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• 제26권4호
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• pp.271-278
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• 2016

Background: This study purposed to analyze the relationship between regional obesity rates and regional variables. Methods: Data was collected from the Korean Statistical Information Service (KOSIS) and Community Health Survey in 2012. The units of analysis were administrative districts such as city, county, and district. The dependent variable was the age-sex adjusted regional obesity rates. The independent variables were selected to represent four aspects of regions: health behaviour factor, psychological factor, socio-economic factor, and physical environment factor. Along with the traditional ordinary least square (OLS) regression analysis model, this study applied geographically weighted regression (GWR) analysis to calculate the regression coefficients for each region. Results: The OLS results showed that there were significant differences in regional obesity rates in high-risk drinking, walking, depression, and financial independence. The GWR results showed that the size of regression coefficients in independent variables was differed by regions. Conclusion: Our results can help in providing useful information for health policy makers. Regional characteristics should be considered when allocating health resources and developing health-related programs.

• 보건행정학회지
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• 제26권1호
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• pp.30-38
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• 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.

• 보건행정학회지
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• 제27권4호
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• pp.296-303
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• 2017

Background: This study purposed to analyze regional factors related to gastric cancer screening rate provided by national cancer screening program in Korea. Methods: The unit of analysis was administrative districts of si gun gu level. Dependent variable was regional gastric cancer screening rate provided by national cancer screening program, and regional variables were selected to represent the regional characteristics such as demographic, health behavior and status, socioeconomic, and health resource. Tobit regression was applied for the analysis. Results: Analysis results showed that gastric cancer screening rate was varied depending on regions from 47.8% to 69.1%. Tobit regression showed that gastric cancer screening rate had negative relationships with smoking rate, financial independence rate, and National Health Insurance premium per capita. And regional gastric cancer screening rate had positive relationships with sex ratio and number of gastric cancer screening center. Conclusion: Regional characteristics should be considered in establishing regional policies for increasing the gastric cancer screening rate.

• 한국경영과학회지
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• 제37권1호
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• pp.29-43
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• 2012

We design a DEA-AR model using multiple regression analysis with new methods which limit weights. When there are multiple input and single output variables, our model can be used, and the weights of input variables use the regression coefficient and coefficient of determination. To verify the effectiveness of the new model, we evaluate the efficiency of the Regional Corporations in Korea. Accordance with statistical analysis, it proved that there is no difference between the efficiency value of the DEA-AR using AHP and our DEA-AR model. Our model can be applied to a lot of research by substituting DEA-AR model relying on AHP in the future.

• 한국수자원학회논문집
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• 제31권1호
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• pp.59-69
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• 1998

빈도별 홍수량의 지역분석을 위하여 유역의 지형특성을 독립변수로 이용하는 회귀모형을 검정하였다. 그런데 이들 독립변수들간의 상관관계가 존재할 경우 능형회귀모형이 이용되기도 하는 이 방법은 다중공선성 문제를 극복하는데 적합한 방법으로 알려져 있다. 능형회귀모형을 최적화하기 위해서는 조정변수가 포함되는 비용함수를 최소화하여야 한다. 본 연구에서는 이 최적화를 위하여 유전알고리즘을 이용하였다. 유전알고리즘은 자연 생물의 유전 및 진화과정을 모방한 추계학적 탐색방법을 말한다. 이러한 유전알고리즘을 이용하여 지역분석 모형을 검정한 결과 안정된 매개변수의 가중치를 얻을 수 있었다.

• 산업진흥연구
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• 제5권3호
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• pp.45-51
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• 2020

본 연구는 빅데이터를 활용하여 투자 및 육성지원이 지역내총생산에 미치는 영향력을 다중회귀분석을 이용하여 분석하였다. 지역내총생산(GRDP)은 각 지역의 생산규모·지출수준·소득수준·산업구조 등을 집약적으로 내포하고 있는 지수로써, 지역경제 분석 및 국가의 정책수립에 활용하는 중요한 자료이다. 국가의 주요 국정과제를 올바르게 수행하기 위해서는 지역경제를 정확히 파악하는 것이 선행되어야 하는데, 이로 인해 최근 지역내총생산에 대한 관심이 급격히 증가하고 있다. 특히 해외투자는 투자유치국의 경제에 미치는 영향력이 상당하여, 이에 대한 많은 실증분석이 이루어지고 있다. 본 연구에서는 해외투자 및 국내육성지원이 지역내총생산에 미치는 영향력을 상관분석과 다중회귀분석을 실시하였으며, 그 결과 전체적으로 투자와 지원이 지역내총생산에 긍정적인 영향을 미친다는 결론을 도출하였다.

• 도시과학
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• 제9권1호
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• pp.41-49
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• 2020

This study analyzed the factors affecting economic growth using multiple regression model and Geographically Weighted Regression in consideration of population, industry and employment, housing and political characteristics on economic growth by region. The analysis results are summarized as follows. First, the total employment growth rate, manufacturing employment growth rate, local election turnout and the level of party consensus between the central and local governments are having a positive impact on regional economic growth. Second, according to the GWR analysis, the population has a positive impact on economic growth in the southern region of Korea, and the increase in the total number of employees has a positive impact on the southern region of Gyeonggi Province, Gangwon Province, North Chungcheong Province and North Gyeongsang Province. Finally, the voter turnout of urbanites is positively affecting economic growth in South Chungcheong Province, Gangwon Province and the southern coast, while North Jeolla and South Jeolla provinces have a positive impact on economic growth as the parties of the central and local governments are equal. The results of this study may suggest the role of local government for regional economic development.

• 보건행정학회지
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• 제30권3호
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• pp.399-408
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• 2020

Background: The purpose of this study was to examine the impact of the regional characteristics on the accessibility of emergency care and the impact of emergency medical accessibility on the patients' prognosis and the emergency medical expenditure. Methods: This study used the 13th beta version 1.6 annual data of Korea Health Panel and the statistics from the Korean Statistical Information Service. The sample included 8,119 patients who visited the emergency centers between year 2013 and 2017. The arrival time, which indicated medical access, was used as dependent variable for multi-level analysis. For ordinal logistic regression and multiple regression, the arrival time was used as independent variable while patients' prognosis and emergency medical expenditure were used as dependent variables. Results: The results for the multi-level analysis in both the individual and regional variables showed that as the number of emergency medical institutions per 100 km² area increased, the time required to reach emergency centers significantly decreased. Ordinal logistic regression and multiple regression results showed that as the arrival time increased, the patients' prognosis significantly worsened and the emergency medical expenses significantly increased. Conclusion: In conclusion, the access to emergency care was affected by regional characteristics and affected patient outcomes and emergency medical expenditure.

• 한국환경과학회지
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• 제8권4호
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• pp.431-441
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• 1999

In this study, the regional frequency analysis is used to determine each subbasin drought frequency with reliable monthly precipitation and the L-Moments method which is almost unbiased and has very nearly a normal distribution is used for the parameter estimation of monthly precipitation time series in Nakdong river basin. As the result of this study, the duration of '93-'94 is most severe drought year than any other water year and the drought frequency is established as compared the regional frequency analysis result of cumulative precipitation of 12th duration months in each subbasin with that of 12th duration months in the major drought duration. The Linear regression equation is induced according to linear regression analysis of drought frequency between Nakdong total basin and each subbasin of the same drought duration. Therefore, as the foundation of this study, it can be applied proposed method and procedure of this study to the water budget analysis considering safety standards for the design of impounding facilities large-scale river basin and for this purpose, above all, it is considered that expansion of reliable preciptation data is needed in watershed rainfall station.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.170-170
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• 2020

Due to the development of technologies, complex computation of huge data set is possible with a prevalent personal computer. Therefore, machine learning methods have been widely applied in the hydrologic field such as regression-based regional frequency analysis (RFA). The main purpose of this study is to compare two frameworks of RFA based on the artificial neural network (ANN) models: quantile regression technique (QRT-ANN) and parameter regression technique (PRT-ANN). As an output layer of the ANN model, the QRT-ANN predicts quantiles for various return periods whereas the PRT-ANN provides prediction of three parameters for the generalized extreme value distribution. Rainfall gauging sites where record length is more than 20 years were selected and their annual maximum rainfalls and various hydro-meteorological variables were used as an input layer of the ANN model. While employing the ANN model, 70% and 30% of gauging sites were used as training set and testing set, respectively. For each technique, ANN model structure such as number of hidden layers and nodes was determined by a leave-one-out validation with calculating root mean square error (RMSE). To assess the performances of two frameworks, RMSEs of quantile predicted by the QRT-ANN are compared to those of the PRT-ANN.