• 제목/요약/키워드: stepwise regression model

검색결과 381건 처리시간 0.025초

Use of big data for estimation of impacts of meteorological variables on environmental radiation dose on Ulleung Island, Republic of Korea

  • Joo, Han Young;Kim, Jae Wook;Jeong, So Yun;Kim, Young Seo;Moon, Joo Hyun
    • Nuclear Engineering and Technology
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    • 제53권12호
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    • pp.4189-4200
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    • 2021
  • In this study, the relationship between the environmental radiation dose rate and meteorological variables was investigated with multiple regression analysis and big data of those variables. The environmental radiation dose rate and 36 different meteorological variables were measured on Ulleung Island, Republic of Korea, from 2011 to 2015. Not all meteorological variables were used in the regression analysis because the different meteorological variables significantly affect the environmental radiation dose rate during different periods, and the degree of influence changes with time. By applying the Pearson correlation analysis and stepwise selection methods to the big dataset, the major meteorological variables influencing the environmental radiation dose rate were identified, which were then used as the independent variables for the regression model. Subsequently, multiple regression models for the monthly datasets and dataset of the entire period were developed.

성인의 생활양식과 건강관련 삶의 질에 대한 연구 (Lifestyle Characteristics and Health Related Quality of Life in Korean Adult)

  • 김애경;김정아
    • 성인간호학회지
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    • 제17권5호
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    • pp.772-782
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    • 2005
  • Objectives: The purpose of this study was to investigate the relationship between Korean lifestyle characteristics and health status and to identify the variables influencing health in Korea. Methods: A cross-sectional descriptive correlational design was used to explore the lifestyle characteristics and health status of 397 Korean adults. Correlational analysis calculated the correlation between lifestyle and health status. To examine the relationship among demographic characteristics, lifestyle, and health status we used the t-test and one-way ANOVA. Stepwise multiple regression was conducted to examine the significant predictors of general health among subjects. Results: Positive correlations were seen between general health (GH) and the overall score and subscales of the Lifestyle. The stepwise regression model showed that vitality (VA), body pain (BP), nutrition, and occupation were significant variables influencing general health (GH). Conclusions: These findings provide evidence regarding the lifestyle patterns and healthstatus among Koreans. When planning intervention strategies for this population, exercise and physical activity should be principal focus areas.

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가족생활주기에 따른 맞벌이 남녀의 대처전략과 결혼만족도 연구 (A Study on the Coping Strategies and Marital Satisfaction of Dual-Earner Men and Women Across the Family Life Cycle)

  • 이은희
    • 한국사회복지학
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    • 제45권
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    • pp.288-314
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    • 2001
  • The purpose of this study is to examine the strategies that may influence the marital satisfaction of dual-earner men and women. General linear model, Pearson's correlation analysis, Stepwise multiple regression were employed for data analysis. the subjects are 396 dual-earner men and women. The result from the research were as follows: 1) coping strategy use differs significantly by life cycle stage. 2) The following strategies significantly correlated with the level of marital satisfaction: cognitive restructuring, delegation. using social support, modifying standards, personal time reducing. 3) The result of stepwise multiple regression analysis indicated that strategies which predict the level of marital satisfaction were cognitive restructuring, delegating, using social support, personal time reducing. these finding give us significant practical implications for social work intervention.

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수정 결정계수를 사용한 로지스틱 회귀모형에서의 변수선택법 (Variable Selection for Logistic Regression Model Using Adjusted Coefficients of Determination)

  • 홍종선;함주형;김호일
    • 응용통계연구
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    • 제18권2호
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    • pp.435-443
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    • 2005
  • 로지스틱 회귀모형에서 결정계수는 선형 회귀모형보다 다양하게 정의되며 그 값들도 매우 작아 로지스틱 회귀모형 평가기준으로 사용되는 통계량이 라고 할 수 없다. Liao와 McGee(2003)는 부적절한 설명변수의 추가 또는 표본크기의 변화에 민감하지 않은 두 종류의 수정 결정계수를 제안하였다. 본 연구에서는 실제자료에 적용한 로지스틱 회귀모형에서 수정 결정계수를 포함한 네 종류의 결정계수들을 변수선택의 기준으로 사용하여 기존의 변수선택 방법인 전진선택, 후진제거, 단계적 선택방법, AIC 통계량 등을 사용한 방법들과 비교하여 그 적절함과 효율성을 토론한다.

미계측유역의 수문모형 매개변수 추정을 위한 하이브리드 지역화모형의 개발 (Development of a hybrid regionalization model for estimation of hydrological model parameters for ungauged watersheds)

  • 김영일;서승범;김영오
    • 한국수자원학회논문집
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    • 제51권8호
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    • pp.677-686
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    • 2018
  • 수문모형의 매개변수 추정에 필요한 유량 관측 자료의 수집은 시 공간적으로 제한이 있어 우리나라도 아직 상당수의 미계측유역이 존재하며, 이를 보완하고자 주변 유역의 정보를 활용하는 지역화 방법들이 연구되어 왔다. 그러나 지역적 특성이나 기후 조건에 따라 지역화 방법의 결과가 상이하여 어느 지역에 어떠한 지역화 방법이 가장 우수하다고 판단하기 어렵다. 본 연구에서는 보편적으로 사용되는 지역화 방법인 지역회귀모형의 설명변수에 공간근접모형으로 추정한 수문모형의 매개변수를 추가하여 회귀모형의 적합성을 향상시켰으며, 이를 하이브리드 지역화모형이라 정의하고 기존 방법들과 비교하였다. 계측유역으로는 관측 자료가 충분한 남한의 37개 유역을 선정하였고, 수문모형은 개념적 수문모형인 GR4J를 사용하였으며, 계측유역에 대한 수문모형의 매개변수 산정은 Shuffled complex evolution 알고리즘을 사용하였다. 유역 특성변수들 간 다중공선성을 고려하기 위해 Variation inflation factor를 사용하였고, Stepwise regression을 통해 회귀모형의 최적 설명변수를 선택하였다. 통계 값을 통해 모형의 적합성을 비교한 결과, 하이브리드 지역화모형에서 가장 작은 RMSE 값을 나타내었으며, 유역별 모의 값의 변동성이 줄어들어 결과의 불확실성 또한 낮아짐을 확인할 수 있었다. 따라서 하이브리드 모형이 미계측유역의 유출량 산정을 위한 하나의 대안이 될 수 있음을 확인하였다.

신호등이 있는 가로망에서의 신호 연동화보정계수 산정모형 (A Model for the Estimation of Progression Adjustment: Factors on a Signal-Controlled Street Network)

  • 김원창;오영태;이승환
    • 대한교통학회지
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    • 제10권2호
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    • pp.25-42
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    • 1992
  • The purpose of this paper is to construct a model to compute a progression adjustment factor on a signalized network. In a way to construct the model, a simulation method is introduced and the TRAF-NETSIM is used as a tool of simulation. The structure of the network chooses an urban arterial network so as to measure the effect of progression and compute average stopped delay on each link. A regression model is constructed by using the results of the simulation. The stepwise variable selection in the regression model in used. The findings of this paper are as follows: i)The secondary queue and platoon ratio are sensitive to the values of the progression adjustment factor ii) The continuous model can practically reflect on various situations in the real world. The platoon adjustment factor can be computed by this model and the data required for this model can be easily obtained in the field.

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Estimating excess post-exercise oxygen consumption using multiple linear regression in healthy Korean adults: a pilot study

  • Jung, Won-Sang;Park, Hun-Young;Kim, Sung-Woo;Kim, Jisu;Hwang, Hyejung;Lim, Kiwon
    • 운동영양학회지
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    • 제25권1호
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    • pp.35-41
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    • 2021
  • [Purpose] This pilot study aimed to develop a regression model to estimate the excess post-exercise oxygen consumption (EPOC) of Korean adults using various easy-to-measure dependent variables. [Methods] The EPOC and dependent variables for its estimation (e.g., sex, age, height, weight, body mass index, fat-free mass [FFM], fat mass, % body fat, and heart rate_sum [HR_sum]) were measured in 75 healthy adults (31 males, 44 females). Statistical analysis was performed to develop an EPOC estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and HR_sum were important variables in the EPOC regression models of various exercise types. The explanatory power and standard errors of estimates (SEE) for EPOC of each exercise type were as follows: the continuous exercise (CEx) regression model was 86.3% (R2) and 85.9% (adjusted R2), and the mean SEE was 11.73 kcal, interval exercise (IEx) regression model was 83.1% (R2) and 82.6% (adjusted R2), while the mean SEE was 13.68 kcal, and the accumulation of short-duration exercise (AEx) regression models was 91.3% (R2) and 91.0% (adjusted R2), while the mean SEE was 27.71 kcal. There was no significant difference between the measured EPOC using a metabolic gas analyzer and the predicted EPOC for each exercise type. [Conclusion] This pilot study developed a regression model to estimate EPOC in healthy Korean adults. The regression model was as follows: CEx = -37.128 + 1.003 × (FFM) + 0.016 × (HR_sum), IEx = -49.265 + 1.442 × (FFM) + 0.013 × (HR_sum), and AEx = -100.942 + 2.209 × (FFM) + 0.020 × (HR_sum).

주택 특성에 대한 내재가격 추정에 관한 연구 (A Study on Estimation the Inplicit Price of Housing Characteristics According to Tenure Type and Region)

  • 제미정
    • 대한가정학회지
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    • 제28권1호
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    • pp.57-66
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    • 1990
  • The purpose of this study was to investigate the analytical model of the implicit price according to objective and subjective characteristics of housing. The hedonic price regression was used for estimating the implicit price. The subjectives of this study were 1,143 dwellers who live in Seoul metropolitan area. Taejeon, and Jeonju. Satistical analyses were conducted using frequencies, percentiles, mean, and multiple regression. The major findings were as follows: 1. There was a significant difference in the implict price of the apartment between owners and renters. 2. There was a sginificant difference in the implicit price of the apartment among Seoul metropolitan area, Taejeon, and Jeonju. 3. Using a stepwise multiple regression method, the order of variables as they were entered in the model were different between tenure types (owner/renter), and regions(Seoul metroplitan area/Taejeon/Jeonju). 4. The linear model was the most appropriate noe which explained the housing price. 5. Subjective characteristics of housing in Taejeon and Jeonju had an effect on the housing price more than those in Seoul metropolitan area.

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아동기 스트레스원과 스트레스 대처행동 및 그 증상에 관한 연구 (Toward an Integrative Approach t the Study of Children's Stress -Stressor, Coping behavior and Symptom-)

  • 정원주
    • 대한가정학회지
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    • 제35권6호
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    • pp.87-99
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    • 1997
  • This study intends to find the effects of children's stress level and coping behaviors on their stress symptoms. The subjects were 840 4-6th grade children in Seoul. The data were analyzed by frequencies, percentages, means, ANOVA, stepwise regression and Cronbach's α. The regression model explained 46% of children's stress symptoms which were affected by coping behaviors(emotional aggression, positive revaluation, seperation for emotional relaxation) and by stressors(children's social-life, individual factors, school-life).

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실시간 수위 예측을 위한 다중선형회귀 모형의 비교 (Comparison of Different Multiple Linear Regression Models for Real-time Flood Stage Forecasting)

  • 최승용;한건연;김병현
    • 대한토목학회논문집
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    • 제32권1B호
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    • pp.9-20
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    • 2012
  • 최근 수위 예측을 위한 개념적 기반, 수문학적, 물리적 기반 모형 등의 단점을 극복하고자 홍수예측을 위해 자료지향형 모형 중의 하나인 다중선형회귀 모형이 널리 도입되고 있다. 본 연구의 목적은 이러한 다중선형회귀 모형의 서로 다른 회귀계수 선정 방법에 따른 홍수예측 성능을 비교 검토하고 이를 통해 적절한 다중회귀 홍수예측 모형을 구축하는 것이다. 이를 위해 입력자료의 자기상관분석을 통해 독립변수의 시간 규모를 결정한 후 최소 자승법, 가중 최소 자승법, 단계별 선택법의 각기 다른 회귀계수 산정 방법을 이용한 홍수예측 모형을 구축하고 중랑천 유역의 다양한 홍수사상에 대해 적용하였다. 구축된 모형들의 성능을 평가하기 위해 평균제곱근오차, Nash-Suttcliffe 효율계수, 평균절대오차, 수정 결정계수와 같이 4개의 통계지표들을 사용하였다. 모의결과 단계별 선택법을 이용한 다중선형회귀 홍수예측 모형이 가장 정확한 예측 결과를 보였고, 최소자승법을 이용한 홍수예측 모형이 가중 최소자승법을 이용한 홍수예측 모형보다 좀 더 나은 예측 결과를 나타냈다.