• Title/Summary/Keyword: OLS(Ordinary Least Square)

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Identification of Uncertainty in Fitting Rating Curve with Bayesian Regression (베이지안 회귀분석을 이용한 수위-유량 관계곡선의 불확실성 분석)

  • Kim, Sang-Ug;Lee, Kil-Seong
    • Journal of Korea Water Resources Association
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    • v.41 no.9
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    • pp.943-958
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    • 2008
  • This study employs Bayesian regression analysis for fitting discharge rating curves. The parameter estimates using the Bayesian regression analysis were compared to ordinary least square method using the t-distribution. In these comparisons, the mean values from the t-distribution and the Bayesian regression are not significantly different. However, the difference between upper and lower limits are remarkably reduced with the Bayesian regression. Therefore, from the point of view of uncertainty analysis, the Bayesian regression is more attractive than the conventional method based on a t-distribution because the data size at the site of interest is typically insufficient to estimate the parameters in rating curve. The merits and demerits of the two types of estimation methods are analyzed through the statistical simulation considering heteroscedasticity. The validation of the Bayesian regression is also performed using real stage-discharge data which were observed at 5 gauges on the Anyangcheon basin. Because the true parameters at 5 gauges are unknown, the quantitative accuracy of the Bayesian regression can not be assessed. However, it can be suggested that the uncertainty in rating curves at 5 gauges be reduced by Bayesian regression.

Comparisons of Kruglyak and Lander's Nonparametric Linkage Test and Weighted Regression Incorporating Replications (KRUGLYAK과 LANDER의 유전연관성 비모수 방법과 반복 자료를 고려한 가중 회귀분석법의 비교)

  • Choi, Eun-Kyeong;Song, Hae-Hiang
    • The Korean Journal of Applied Statistics
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    • v.21 no.1
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    • pp.1-17
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    • 2008
  • The ordinary least squares regression method of Haseman and Elston(1972) is most widely used in genetic linkage studies for continuous traits of sib pairs. Kruglyak and Lander(1995) suggested a statistic which appears to be a nonparametric counterpart to the Haseman and Elston(1972)'s regression method, but in fact these two methods are quite different. In this paper the relationships between these two methods are described and will be compared by simulation studies. One of the characteristics of the sib-pair linkage study is that the explanatory variable has only three different values and thus dependent variable is heavily replicated in each value of the explanatory variable. We propose a weighted least squares regression method which is more appropriate to this situation and the efficiency of the weighted regression in genetic linkage study was explored with normal and non-normal simulated continuous traits data. Simulation studies demonstrated that the weighted regression is more powerful than other tests.

Testing Non-Stationary Relationship between the Proportion of Green Areas in Watersheds and Water Quality using Geographically Weighted Regression Model (공간지리 가중회귀모형(GWR)을 이용한 유역 녹지비율과 하천수질의 비균질적 관계 검증)

  • Lee, Sang-Woo
    • Journal of the Korean Institute of Landscape Architecture
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    • v.41 no.6
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    • pp.43-51
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    • 2013
  • This study aims to examine the presence of non-stationary relationship between water quality and land use in watersheds. In investigating the relationships between land use and water quality, most previous studies adopted OLS method which is assumed stationarity. However, this approach is difficult to capture the local variation of the relationships. We used 146 sampling data and land cover data of Korean Ministry of Environment to build conventional regressions and GWR models for BOD, TN and TP. Regression model and GWR models of BOD, TN, TP were compared with $R^2$, AICc and Moran's I. The results of comparisons and descriptive statistics of GWR models strongly indicated the presence of Non-Stationarity between water quality and land use.

A Study on the Factors Determining Officetel Price in Busan (부산지역 오피스텔 가격 결정요인 분석)

  • Choi, Yeol;Kim, Hyeong Jun;Yeo, Jung Hoon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.35 no.3
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    • pp.725-735
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    • 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.

A Study on the Regional Factors Affecting the Death Rates of Cardio-Cerebrovascular Disease Using the Spatial Analysis (공간분석을 이용한 심뇌혈관질환 사망률에 영향을 미치는 지역요인 분석)

  • Park, Young Yong;Park, Ju-Hyun;Park, You-Hyun;Lee, Kwang-Soo
    • Health Policy and Management
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    • v.30 no.1
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    • pp.26-36
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    • 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.

A Spatial Statistical Approach on the Correlation between Walkability Index and Urban Spatial Characteristics -Case Study on Two Administrative Districts, Busan- (도시 공간특성과 Walkability Index의 상관성에 관한 공간통계학적 접근 -부산광역시 2개 구를 대상으로-)

  • Choi, Don Jeong;Suh, Yong Cheol
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.4_1
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    • pp.343-351
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    • 2014
  • The correlation between regional Walkability Index and their physical socio-economic characteristics has evaluated by the spatial statistical analysis to understand the urban pedestrian environments, where has been emerging the significance, recently. Following to the study, the Walkability Indexes were calculated quantitatively from two administrative districts of Busan and measured Global Local spatial autocorrelation indices. Additionally, the Geographically Weighted Regression model was applied to define the correlation between Walkability Indexes and urban environmental variables. The spatial autocorrelation values and clusters on the Walkability Indexes were derived in statistically significant level. Furthermore, the Geographically Weighted Regression model has been derived more improved inference than the OLS regression model, so as the influence of local level pedestrian environment was identified. The results of this study suggest that the spatial statistical approach can be effective on quantitative assessing the pedestrian environment and navigating their associated factors.

The Moderating Role of Ownership Concentration on the Relationship between Board Composition and Saudi Bank Performance

  • HABTOOR, Omer Saeed
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.10
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    • pp.675-685
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    • 2020
  • The main purpose of this study is to investigate the potential effect of ownership concentration on the relationship between board composition and bank performance. The study employs a sample of Saudi banks listed on Saudi stock exchange (TADAUWL) over the period from 2011 to 2018. To test the study hypotheses and control for endogeneity issues, the Ordinary Least Square (OLS) and the Two-Stage Least Squares (2SLS) techniques are used. The empirical results reveal a significant negative moderating effect of ownership concentration on the association between board composition and bank performance, which confirms the study argument and supports hypotheses. The results indicate that board composition in terms of independent board members, executive board members, and non-executive board members in banks with higher ownership concentration have a weaker positive influence on bank performance. For control variables, the results are almost consistent with theoretical perspectives and previous empirical evidence. The results of this study have important implications for regulatory authorities, companies, and market participants in Saudi Arabia and countries with high concentrated ownership to understand how ownership concentration could affect corporate governance and firm performance and to identify appropriate actions to protect board composition from the influence of ownership concentration.

Identifying Key Factors to Affect Bus Headway Deviation using Hierarchical Linear Model (Seoul Case Study) (HLM을 이용한 버스차두간격 편차에 미치는 요인분석 (서울시사례를 중심으로))

  • Lee, Ho-Sang;Kim, Do-Gyeong;Kim, Yeong-Chan;Hwang, Gyeong-Su
    • Journal of Korean Society of Transportation
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    • v.27 no.6
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    • pp.119-127
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    • 2009
  • It has been known that bus route and company related characteristics have influences on punctuality, but fewer research have been conducted. Independent variables used in this study were selected using correlation analysis, and OLS(Ordinary Least Square) and HLM(Hierarchical Linear Model) were employed to identify factors affecting bus punctuality(headway deviation). The results showed that ICC(intraclass Correlation Coefficient) is 0.10, indicating that hierarchical linear models are more adequate for these data because there is effective variation in the subjects between companies. Punctuality was found to be negatively associated with the number of vehicles, the number of persons per vehicle, and total travel time. On the other hand, average headway and company size have a positive relationship with punctuality. Therefore, the number of vehicles per route, average headway, and the number of vehicles managed by a company should be considered for more accurately evaluating the management of piunctuality.

Geographically Weighted Regression on the Characteristics of Land Use and Spatial Patterns of Floating Population in Seoul City (서울시 유동인구 분포의 공간 패턴과 토지이용 특성에 관한 지리가중 회귀분석)

  • Yun, Jeong Mi;Choi, Don Jeong
    • Journal of Korean Society for Geospatial Information Science
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    • v.23 no.3
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    • pp.77-84
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    • 2015
  • The key objective of this research is to review the effectiveness of spatial regression to identify the influencing factors of spatial distribution patterns of floating population. To this end, global and local spatial autocorrelation test were performed using seoul floating population survey(2014) data. The result of Moran's I and Getis-Ord $Gi^*$ as used in the analysis derived spatial heterogeneity and spatial similarities of floating population patterns in a statistically significant range. Accordingly, Geographically Weighted Regression was applied to identify the relationship between land use attributes and population floating. Urbanization area, green tract of land of micro land cover data were aggregated in to $400m{\times}400m$ grid boundary of Seoul. Additionally public transportation variables such as intersection density transit accessibility, road density and pedestrian passage density were adopted as transit environmental factors. As a result, the GWR model derived more improved results than Ordinary Least Square(OLS) regression model. Furthermore, the spatial variation of applied local effect of independent variables for the floating population distributions.

Environmental Equity Analysis of Fine Dust in Daegu Using MGWR and KT Sensor Data (다중 스케일 지리가중회귀 모형과 KT 측정기 자료를 활용한 대구시 미세먼지에 대한 환경적 형평성 분석)

  • Euna CHO;Byong-Woon JUN
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.4
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    • pp.218-236
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    • 2023
  • This study attempted to analyze the environmental equity of fine dust(PM10) in Daegu using MGWR(Multi-scale Geographically Weighted Regression) and KT(Korea Telecom Corporation) sensor data. Existing national monitoring network data for measuring fine dust are collected at a small number of ground-based stations that are sparsely distributed in a large area. To complement these drawbacks, KT sensor data with a large number of IoT(Internet of Things) stations densely distributed were used in this study. The MGWR model was used to deal with spatial heterogeneity and multi-scale contextual effects in the spatial relationships between fine dust concentration and socioeconomic variables. Results indicate that there existed an environmental inequity by land value and foreigner ratio in the spatial distribution of fine dust in Daegu metropolitan city. Also, the MGWR model showed better the explanatory power than Ordinary Least Square(OLS) and Geographically Weighted Regression(GWR) models in explaining the spatial relationships between the concentration of fine dust and socioeconomic variables. This study demonstrated the potential of KT sensor data as a supplement to the existing national monitoring network data for measuring fine dust.