• Journal of Preventive Medicine and Public Health
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• 제24권1호
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• pp.29-36
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• 1991

A multiple regression analysis using ordinary least square (OLS) is frequently used for the projection of health expenditure as well as for the identification of factors affecting health care costs. Data for the analysis often have mixed characteristics of time series and cross section. Parameters as a result of OLS estimation, in this case, are no longer the best linear unbiased estimators (BLUE) because the data do not satisfy basic assumptions of regression analysis. The study theoretically examined statistical problems induced when OLS estimation was applied with the time series cross section data. Then both the OLS regression and time series cross section regression (TSCS regression) were applied to the same empirical da. Finally, the difference in parameters between the two estimations were explained through residual analysis.

• 한국항공운항학회지
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• 제27권3호
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• pp.98-105
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• 2019

In the past 30 years, our aviation demand has been growing continuously. As such, the importance of the demand forecasting field is increasing. In this study, the factors influencing Korea's international air demand were selected, and the international air demand was analyzed, forecasted and reviewed through OLS multiple regression analysis. As a result, passenger demand was affected by GDP per capita, oil price and exchange rate, while cargo demand was affected by GDP per capita and private consumption growth rate. In particular, passenger demand was analyzed to be sensitive to temporary external shocks, and cargo demand was more affected by economic variables than temporary external shocks. Demand forecasting, OLS multiple regression analysis, passenger demand, cargo demand, transient external shocks, economic variables.

• 대한공간정보학회지
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• 제20권3호
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• pp.57-63
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• 2012

정규최소자승법(OLS : Ordinary Least Square)은 장수인구의 지역적 분포와 적용된 환경변수들의 관계가 공간상에서 동일하다고 가정한다. 따라서 장수현상이나 그와 관련된 변수의 공간적 특성을 충분히 설명할 수 없다. 지리가중 회귀분석(GWR : Geographically Weighted Regression)모형은 지리적 가중 함수를 통해 인접지역들의 공간적 유사성을 대변할 수 있다. 또한 환경특성에 따른 장수인구분포의 공간적 변이를 국지적으로 설명할 수 있는 특징이 있다. 이러한 관점에서 본 논문은 기존의 연구에서 제시된 장수의 환경생태학적 요인들에 대해 보통 최소자승법과 GWR모델간의 비교분석을 수행하였다. 연구결과 GWR모형이 OLS모형보다 높은 모형 부합도를 가지고 특정 환경 변수가 가지는 효과에 대한 공간적 변동성을 설명할 수 있는 것으로 나타났다.

• 한국측량학회지
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• 제37권3호
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• pp.129-141
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• 2019

최근 급속도로 성장하는 도시에는 많은 인구와 시설물들이 증가하고 집중이 심화함에 따라 재해와 재난에 취약함을 나타낸다. 특히, 화재는 우리나라의 도시 내에서 교통사고와 더불어 가장 많이 발생하는 재해 중 하나로 많은 인명 및 재산피해를 준다. 따라서 본 연구에서는 화재 발생에 대한 영향요인을 분석하기 위해 진주시를 대상으로 2007년부터 2017년까지 10년간 화재데이터를 취득하였다. 먼저 공간 자기 상관성 분석을 시행하여 진주시 화재 발생의 공간 분포 패턴을 파악한 후, 상관관계 및 다중 회귀 분석을 통해 인문 사회 요인과 물리적 요인 간의 공간적 종속성 및 비정상성을 확인하였고 이를 토대로 화재 발생 위치와 각 요인별 위치를 고려하여 공간 가중치를 활용한 OLS 회귀 분석을 실시하였다. 그 결과로 첫째, 진주시 화재 발생의 LISA분석 결과 화재 발생 빈도가 높은 용도지역은 중심상업지역, 공업지역, 주거지역 순으로 나타났다. 둘째, 인구 사회적 변수 및 물리적 변수를 통합하여 다중회귀분석의 최종 모형으로 도출된 요인들을 중심으로 공간가중치를 적용하여 OLS회귀모형을 분석한 결과 제2종 근린생활시설이 화재 발생과 가장 높은 상관성을 보였으며 다음으로 단독주택, 판매시설, 제1종 근린생활시설, 가구수의 순으로 상관성이 있는 것으로 분석되었다. 이러한 연구 결과를 통해 도시 지역의 시설물별 화재 발생 요인을 분석하고 화재 안전대책을 수립하는데 유용한 자료로 활용될 것으로 예상된다.

• Communications for Statistical Applications and Methods
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• 제19권2호
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• pp.293-301
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• 2012

Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.

• 한국측량학회지
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• 제36권6호
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• pp.611-620
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• 2018

도시재생사업의 활성화와 함께 주요 사업대상이 되고 있는 골목상권에 대한 사회적 관심이 커지고 있다. 골목상권 재생 방안을 마련하기 위해서는 어떤 고객이 얼마나 많이 매출을 발생시키는 지를 파악하는 것이 무엇보다 중요하다. 이에 본 연구에서는 고객특성이 골목상권 매출액에 미치는 영향을 분석하고자 한다. OLS 회귀분석 결과, 종속변수인 골목상권 매출액과 독립변수인 고객특성, 입지특성, 구조특성의 관계가 상권위치에 따라 달라지는 공간적 이질성이 확인되어 본 연구에서는 대안으로 지리가중회귀분석을 수행한다. 모형 적합도를 $R^2$과 AICc를 통해 비교한 결과, 지리가중회귀분석이 OLS 회귀분석보다 더 우수한 것으로 나타났다. OLS 회귀분석을 통해 여성고객 비율과 40-50대 고객비율, 골목상권 내 종사자수, 사업체 창업률, 건축물 밀도, 골목상권 면적이 정의 영향을 주는 반면 20-30대 고객비율, 지하철역과의 거리, 버스정류장과의 거리는 부의 영향을 주는 것으로 나타났다. 지리가중회귀분석의 국지적 회귀계수 값들을 골목상권별로 비교한 결과, 여성고객 비율은 서북권 골목상권 매출액에 가장 큰 영향을 주며 서남권과 도심권, 동북권은 그 다음으로 나타났다. 20-30대 고객비율과 40-50대 고객 비율은 동남권과 동북권 골목상권 매출액에 큰 영향을 주며 서남권은 그 다음으로 나타났다. 본 연구는 고객특성 중 성별과 연령에 한정된 분석만 수행했다는 점에서 한계를 갖지만 골목상권별로 매출액 영향 요인을 식별함으로써 상권 활성화방안 수립과 도시재생사업에 도움을 줄 수 있을 것으로 기대가 된다.

• 보건의료산업학회지
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• 제8권2호
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• pp.11-22
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• 2014

This study purposed to analyze the regional variation of the local-out rates of inpatient services. Multiple data sources collected from National Health Insurance Corporation and statistics Korea were merged to produce the analysis data set. The unit of analysis in this study was city, Gun, Gu, and all of them were included in analysis. The dependent variable measured the local-out rate of inpatient cost in study regions. Local environments were measured by variables in three dimensions: provider factors, socio-demographic factors, and health status. Along with the traditional ordinary least square (OLS) based regression model, geographically weighted regression (GWR) model were applied to test their effects. SPSS v21 and ArcMap v10.2 were applied for the statistical analysis. Results from OLS regression showed that most variables had significant relationships with the local-out rate of inpatient services. However, some variables had shown diverse directions in regression coefficients depending on regions in GWR. This implied that the study variables might not have consistent effects and they may varied depending the locations.

• 한국항공운항학회지
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• 제29권2호
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• pp.106-110
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• 2021

In this study, the main factors affecting the number of passengers and cargo volume transported by air between Korea, China and Japan over the past 20 years are to be identified. For the analysis, data from three countries' GDP and per capita as well as exchange rates and international oil prices were used, and OLS multiple regression analysis and fixed effect analysis were performed. As a result of the analysis, both the number of passengers and cargo volume transported by air showed a negative (-) direction for GDP, which represents the country's economic power, and a positive (+) direction, for per capita GDP, which represents income level. And the increase in the exchange rate between China and Japan acted in a positive (+) direction on the increase in the number of passengers, and the effect of oil prices was found to be limited.

• 한국항공운항학회지
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• 제29권3호
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• pp.111-116
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• 2021

This study aims to identify the representative factors affecting the air trade between the two countries over the past 20 years, targeting China, Korea's largest trading partner for air transport. In the analysis, the two countries' GDP, GDP per capita, and tariff rates, as well as exchange rates, international oil prices, and FTAs were used as variables. For the analysis method, OLS multiple regression analysis was performed, and each was analyzed by dividing the export amount, import amount, and trade amount. As a result of the analysis, China's GDP and Korea's GDP per capita showed a positive (+) direction, an increase in the exchange rate resulted in an increase in the amount of trade, and an increase in the tariff rate resulted in a decrease in the amount of trade. Whether the FTA was concluded or not acted as a factor in increasing the amount of trade between the two countries.

• 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.