• 제목/요약/키워드: REGRESSION ANALYSIS

검색결과 23,982건 처리시간 0.049초

회귀분석에 의한 TOC 농도 추정 - 오수천 유역을 대상으로 - (Application of Regression Analysis Model to TOC Concentration Estimation - Osu Stream Watershed -)

  • 박진환;문명진;한성욱;이형진;정수정;황경섭;김갑순
    • 환경영향평가
    • /
    • 제23권3호
    • /
    • pp.187-196
    • /
    • 2014
  • The objective of this study is to evaluate and analyze Osu stream watershed water environment system. The data were collected from January 2009 to December 2011 including water temperature, pH, DO, EC, BOD, COD, TOC, SS, T-N, T-P and discharge. The data were used for principle component analysis and factor analysis. The results are as followes. The primary factors obtained from both the principal component analysis and the factor analysis were BOD, COD, TOC, SS and T-P. Once principal component analysis and factor analysis have been performed with the collected data and then the results will be applied to both simple regression model and multiple regression model. The regression model was developed into case 1 using concentrations of water quality parameters and case 2 using delivery loads. The value of the coefficient of determination on case 1 fell between 0.629 and 0.866; this was lower than case 2 value which fell between 0.946 and 0.998. Therefore, case 2 model would be a reliable choice.The coefficient of determination between the estimated figure using data which was developed to the regression model in 2012 and the actual measurement value was over 0.6, overall. It can be safely deduced that the correlation value between the two findings was high. The same model can be applied to get TOC concentrations in future.

MS Excel 함수들을 이용한 회귀 분석 모형 추정 및 관계 분석 검정을 위한 매크로 개발 (지하철 전기요금 자료 회귀분석에 응용) (Development of MS Excel Macros to estimate regression models and test hypotheses of relationships between variables (Application to regression analysis of subway electric charges data))

  • 김숙영
    • 한국컴퓨터산업학회논문지
    • /
    • 제10권5호
    • /
    • pp.213-220
    • /
    • 2009
  • 변수들간의 관계 모형을 설정하고 관계성 유무를 분석하는 회귀 분석은 거의 모든 조사 연구 및 실험연구들에서 필수적인 통계 분석 방법이다. 자료는 독립변수와 종속변수로 구성되므로 쌍으로 취급되며 모든 통계량 계산은 행렬 연산에 의하여 수행된다. 변수들 관계를 가장 잘 설명하는 모형 설정에 따라 회귀분석 결과의 정확성이 평가되므로 자료 수치들을 XY 평면상에서 점을 찍어 가장 적합한 함수 모형을 선택해야 한다. MS 엑셀의 그래픽 및 행렬 연산 기능의 메뉴들을 사용하면 수집된 자료에 가장 적합한 모형을 설정하고 필요한 모든 가설검정 작업을 쉽게 수행할 수 있다. 본 연구에서는 회귀 분석의 모형 설정 및 가설검정 결과들을 산출하는 엑셀 함수를 이용한 매크로를 개발하였다. 본 연구에서 개발한 회귀분석 매크로를 한 개의 종속변수와 3개의 독립 변수를 가진 지하철 전기요금 자료 분석에 적용하여 얻은 결과와 엑셀에 내장된 통계 회귀분석 메뉴를 적용한 결과를 비교한다.

  • PDF

풍속 예측을 위한 선형회귀분석과 비선형회귀분석 기법의 비교 및 인자분석 (Comparison of Linear and Nonlinear Regressions and Elements Analysis for Wind Speed Prediction)

  • 김동연;서기성
    • 한국지능시스템학회논문지
    • /
    • 제25권5호
    • /
    • pp.477-482
    • /
    • 2015
  • 단기풍속 예측을 위한 진화적 선형 및 비선형 회귀분석 기반의 보정 기법을 비교한다. 모델의 체계적 오류를 교정하기 위한 효율적인 MOS(Model Output Statistics)의 개발이 필요하나, 기존의 선형회귀분석 기반의 보정기법은 다양한 기상요소의 복잡한 비선형 특성을 반영하기 힘들다. 이를 개선하기 위해서 유전 프로그래밍을 사용하여 풍속 예측에 대한 비선형 보정 수식을 생성하는 기법을 제안하고 기본 다중선형회귀분석법 및 Ridge, Lasso 회귀분석법과 비교한다. 더불어, 선형회귀분석법과 진화적 비선형회귀분석 기법의 인자 선택의 차이와 유사성을 비교하고 분석한다. 2007년~2013년의 KLAPS(Korea Local Analysis and Prediction System) 재분석자료를 사용하여 제주도와 부산지역의 격자점에 대한 실험을 수행한다.

韓國河川의 月 流出量 推定을 위한 地域化 回歸模型 (Regionalized Regression Model for Monthly Streamflow in Korean Watersheds)

  • 김태철;박성우
    • 한국농공학회지
    • /
    • 제26권2호
    • /
    • pp.106-124
    • /
    • 1984
  • Monthly streanflow of watersheds is one of the most important elements for the planning, design, and management of water resources development projects, e.g., determination of storage requirement of reservoirs and control of release-water in lowflow rivers. Modeling of longterm runoff is theoretically based on water-balance analysis for a certain time interval. The effect of the casual factors of rainfall, evaporation, and soil-moisture storage on streamflow might be explained by multiple regression analysis. Using the basic concepts of water-balance and regression analysis, it was possible to develop a generalized model called the Regionalized Regression Model for Monthly Streamflow in Korean Watersheds. Based on model verification, it is felt that the model can be reliably applied to any proposed station in Korean watersheds to estimate monthly streamflow for the planning, design, and management of water resources development projects, especially those involving irrigation. Modeling processes and properties are summarized as follows; 1. From a simplified equation of water-balance on a watershed a regression model for monthly streamflow using the variables of rainfall, pan evaporation, and previous-month streamflow was formulated. 2. The hydrologic response of a watershed was represented lumpedly, qualitatively, and deductively using the regression coefficients of the water-balance regression model. 3. Regionalization was carried out to classify 33 watersheds on the basis of similarity through cluster analysis and resulted in 4 regional groups. 4. Prediction equations for the regional coefficients were derived from the stepwise regression analysis of watershed characteristics. It was also possible to explain geographic influences on streamflow through those prediction equations. 5. A model requiring the simple input of the data for rainfall, pan evaporation, and geographic factors was developed to estimate monthly streamflow at ungaged stations. The results of evaluating the performance of the model generally satisfactory.

  • PDF

Fused inverse regression with multi-dimensional responses

  • Cho, Youyoung;Han, Hyoseon;Yoo, Jae Keun
    • Communications for Statistical Applications and Methods
    • /
    • 제28권3호
    • /
    • pp.267-279
    • /
    • 2021
  • A regression with multi-dimensional responses is quite common nowadays in the so-called big data era. In such regression, to relieve the curse of dimension due to high-dimension of responses, the dimension reduction of predictors is essential in analysis. Sufficient dimension reduction provides effective tools for the reduction, but there are few sufficient dimension reduction methodologies for multivariate regression. To fill this gap, we newly propose two fused slice-based inverse regression methods. The proposed approaches are robust to the numbers of clusters or slices and improve the estimation results over existing methods by fusing many kernel matrices. Numerical studies are presented and are compared with existing methods. Real data analysis confirms practical usefulness of the proposed methods.

An Approach to Applying Multiple Linear Regression Models by Interlacing Data in Classifying Similar Software

  • Lim, Hyun-il
    • Journal of Information Processing Systems
    • /
    • 제18권2호
    • /
    • pp.268-281
    • /
    • 2022
  • The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

로지스틱 회귀분석과 다수준 분석을 이용한 Craniotomy 환자의 사망률 평가결과의 일치도 분석 (Comparing Risk-adjusted In-hospital Mortality for Craniotomies : Logistic Regression versus Multilevel Analysis)

  • 김선희;이광수
    • 보건의료산업학회지
    • /
    • 제9권2호
    • /
    • pp.81-88
    • /
    • 2015
  • The purpose of this study was to compare the risk-adjusted in-hospital mortality for craniotomies between logistic regression and multilevel analysis. By using patient sample data from the Health Insurance Review & Assessment Service, in-patients with a craniotomy were selected as the survey target. The sample data were collected from a total number of 2,335 patients from 90 hospitals. The sample data were analyzed with SAS 9.3. From the results of the existing logistic regression analysis and multilevel analysis, the values from the multilevel analysis represented a better model than that of logistic regression. The intra-class correlation (ICC) was 18.0%. It was found that risk-adjusted in-hospital mortality for craniotomies may vary in every hospital. The agreement by kappa coefficient between the two methods was good for the risk-adjusted in-hospital mortality for craniotomies, but the factors influencing the outcome for that were different.

ANCOVA 모형을 위한 DD-plot (DD-Plot for ANCOVA Models)

  • 장대흥
    • 응용통계연구
    • /
    • 제27권2호
    • /
    • pp.227-237
    • /
    • 2014
  • 우리는 회귀분석에서 설명변수들 중 일부가 질적 변수인 경우 지시변수를 사용한다. 또한 공분산분석모형에서는 관심인자의 효과에 대한 유의성 검정시 연속변수인 공변수로 주어지는 방해인자를 미리 회귀분석으로 제거한다. 지시변수 사용 회귀모형이나 공분산분석모형을 위한 확증적 자료분석 전에 탐색적 자료분석의 한 수단으로서 자료깊이에 근거한 DD-plot을 이용하면 집단 간의 차이를 쉽게 알아볼 수 있다. 이 방법은 오차항의 통계모형을 가정하지 않으므로 유용한 탐색적 방법이 될 수 있다. 몇 가지 사례들을 통하여 DD-plot이 지시변수 사용 회귀모형이나 공분산분석모형을 위한 그래픽 탐색적 자료분석방법으로서 유용함을 보였다.

FACTORS AFFECTING PATIENTS' DECISION-MAKING FOR DENTAL PROSTHETIC TREATMENT

  • Jung, Hyo-Kyung;Kim, Han-Gon
    • 대한치과보철학회지
    • /
    • 제46권6호
    • /
    • pp.610-619
    • /
    • 2008
  • STATEMENT OF PROBLEM: Factors affecting patients' decision-making for dental prosthetic treatment should be examined in terms of understanding improving patients' oral health. PURPOSE: The main purpose of this dissertation was to investigate patients' dental prosthetic treatment and factors affecting patients' decision-making for dental prosthesis treatment in Deagu and Gyungbook areas. MATERIAL AND METHODS: This study was based on the preliminary survey of dental patients conducted from July 1 to August 31 in 2006. A total of 700 questionnaires had been distributed and 640 were collected. 629 questionnaires were used for the statistical analysis. Descriptive and inferential statistics, such as frequencies, cross tabulation analysis, correlation analysis, logistic regression analysis, and multiple regression analysis were introduced. In the multiple regression analysis and logistic regression analysis, twenty-two independent variables were employed to explore the factors which have impacts on decision-making and satisfaction. RESULTS: The results of this dissertation are as follows: Logistic regression analysis turned out that monthly income, age, degree of expectation, marital status, and employer-insured policy of national insurance statistically increased the odds of decision-making of dental prosthesis treatment. But educational attainment decreased the odds ratio of the decision-making of dental prosthesis treatment. However, the rest independent variables do not have statistically significant impacts on the decision-making of dental prosthesis treatment CONCLUSION: Among independent variables, marital status had the most significant influence on the decision making of dental prosthesis treatment. Finally, suggestions for the future study and policy implications to improve satisfaction of the patients' dental prosthetic treatment were discussed.