• Title/Summary/Keyword: 중회귀 분석

Search Result 4,182, Processing Time 0.033 seconds

A Study on the Influence of the Characteristics of Planning on the Cost of Apartment (공동주택의 계획특성이 분양원가에 미치는 영향에 대한 분석)

  • Kim, Gwang-Ho
    • Korean Journal of Construction Engineering and Management
    • /
    • v.7 no.1 s.29
    • /
    • pp.89-99
    • /
    • 2006
  • Usually feasibility analysis in a narrow sense is a economic analysis of project. Feasibility analysis focused in this study is confined to the matter of finance. Many studies have been executed in qualitative element which include decision-making process or prediction of housing market. But it is difficult to find economic analysis related to characteristics of planning. In this study, floor area ratio, selling area ratio and term of works are adopted as the Characteristics of Planning. So, the purpose of this study is to analyze the Influence of the characteristics of planning on the cost of apartment by means of multiple regression analysis and what-if method.

Conversion Factor for Determinating Carbon Contents from Organic Matter Contents in Composts by Ignition Method (회화법으로 측정한 퇴비중 유기물 함량을 탄소 함량으로 변환하기 위한 환산계수 결정)

  • Nam, Jae-Jak;Cho, Nam-Jun;Jung, Kwang-Yong;Lee, Sang-Hak
    • Korean Journal of Soil Science and Fertilizer
    • /
    • v.31 no.4
    • /
    • pp.380-383
    • /
    • 1998
  • For the evaluation of the quality of compost, the determination of C/N ratio is mandatory in Korea. Accordingly it is necessary to measure the total carbon content of compost for the quality control of composts. It is, however, not easy to measure the carbon content of compost. For practical purposes total carbon content of compost can be estimated from the total organic matter content, which is estimated by way of ignition loss. For this, it is necessary to establish the factor for conversion of organic matter into carbon. We studied the relationship between the organic matter content determined by ignition method and total carbon content measured by elemental analyzer using 160 compost sample collected from the markets. The relationship between the carbon content and organic matter in those composts was found to be "y(% carbon)=1.995+0.484%(% organic matter)"($r^2=0.943$). This result suggests that total carbon contents of composts can be estimated from the organic matter content.

  • PDF

The Life Satisfaction Analysis of Middle School Students Using Korean Children and Youth Panel Survey Data (한국아동·청소년패널조사 데이터를 이용한 중학생 삶의 만족도 분석)

  • An, Ji-Hye;Yun, You-Dong;Lim, Heui-Seok
    • Journal of Digital Convergence
    • /
    • v.14 no.2
    • /
    • pp.197-208
    • /
    • 2016
  • In this paper, data mining regression analysis and decision tree analysis techniques were used to analyze factors affecting the life satisfaction of middle school students. For this purpose, we analyzed Korean Children and Youth Panel Survey(KCYPS) data. As results, the common influencing factors to the life satisfaction were derived from regression analysis. Those factors are self-esteem, depression, total grade satisfaction, regional community awareness, career identity, annual delinquency damage experience, siblings' factors, trust, behavioral control, and concentration. Based on the result described by decision tree analysis, the factors that indicate a significant impact on the life satisfaction of middle school students were self-esteem, depression, career identity and attention factor.

Graphical regression and model assessment in logistic model (로지스틱모형에서 그래픽을 이용한 회귀와 모형평가)

  • Kahng, Myung-Wook;Kim, Bu-Yong;Hong, Ju-Hee
    • Journal of the Korean Data and Information Science Society
    • /
    • v.21 no.1
    • /
    • pp.21-32
    • /
    • 2010
  • Graphical regression is a paradigm for obtaining regression information using plots without model assumptions. The general goal of this approach is to find lowdimensional sufficient summary plots without loss of important information. Model assessments using residual plots are less likely to be successful in models that are not linear. As an alternative approach, marginal model plots provide a general graphical method for assessing the model. We apply the methods of graphical regression and model assessment using marginal model plots to the logistic regression model.

Calculation Of Critical Stress On Jointed Concrete Pavement By Using Neural Networks & Linear Regression Models (뉴럴 네트워크 및 선형 회귀식을 이용한 줄눈 콘크리트 포장의 한계 응력 계산)

  • Kang, Tae-Wook;Ryu, Sung-Woo;Kim, Seong-Min;Cho, Yoon-Ho
    • International Journal of Highway Engineering
    • /
    • v.10 no.3
    • /
    • pp.129-138
    • /
    • 2008
  • The finite element method(FEM) was one of tools used to solve problem of previous Concrete Pavement and was applied to Korea Pavement Research Program Study. This study used the ABAQUS and the fortran analysis program to calculate the critical stress on jointed concrete pavement and compared and analyzed the results by using neural networks and linear regression model. In that case, which are not enough analysises by using FEM programs though many input variables, when the results of FEM with NN and linear regression models are compared, there are some differences. The other cases, which are reduced input variables and a lot of analysises each of them, results of Neural Networks(NN) and linear regression models are simulated to them of FEM. But, the result of NN is more exact than them of linear regression at the (0,0), (1,1). On the results of this study, it is suggested that the calculation of stress using NN is more compatible to Korea Pavement Research Program Study.

  • PDF

A Study on Wheel Load Distribution Factors of Skew Steel Box Girder Bridges (강상자형 사교의 윤하중분배계수)

  • Seo, Chang-Bum;Song, Jae-Ho;Kim, Il-Soo
    • Journal of the Korea institute for structural maintenance and inspection
    • /
    • v.13 no.4 s.56
    • /
    • pp.148-158
    • /
    • 2009
  • Firstly the problems of existing foreign code concerning wheel load distribution factor for skew box girder bridges have been examined, and the main parameters which have effects on wheel load distribution factors are evaluated in this study. Further finite element analyses on various skew steel box girder bridges are carried out. Based on the analysis results, formulas to determine wheel load distribution factors are proposed using multiple regression analysis. It is found when using the proposed formulas in this study weak points of existing specifications could be improved and also time spent at structural analysis should be saved a lot, so that the validity and practicality could be verified.

Information Arrival and Stock Market Volatility Dynamics (정보(情報)의 발생(發生)과 주가(株價)의 변동성(變動性))

  • Rhee, Il-King
    • The Korean Journal of Financial Management
    • /
    • v.16 no.2
    • /
    • pp.285-308
    • /
    • 1999
  • 증권의 가격형성에 유리한 뉴스와 불리한 뉴스가 도착할 때 이 뉴스가 주가의 변동성에 미치는 영향의 정도는 차이가 있다. 불리한 뉴스가 변동성에 미치는 영향도가 유리한 뉴스가 변동성에 미치는 영향도보다 크다. 따라서 불리한 뉴스가 발생할 때 형성되는 변동성의 양이 유리한 뉴스의 도착시보다 크다. 그리고 충격의 크기에 따라 이 충격이 야기하는 변동성의 양의 크기에도 차이가 존재한다. 일반 자기회귀 조건부 이분산 과정은 유리한 뉴스와 불리한 뉴스를 대칭적으로 반영하고 있다. 이 뉴스들을 비대칭적으로 포착하는 자기회귀 조건부 이분산 과정의 모형들을 실증적으로 분석하였다. 뉴스의 비대칭성과 규모를 적절히 포착하고 있는 모형들이 비선형 일반 자기회귀 조건부 이분산 과정, 지수 일반 자기회귀 조건부 이분산 과정과 정보 포착 자기회귀 조건부 이분간 과정임이 발견되었다. 이 중 비선형 일반 자기회귀 조건부 이분산 과정이 가장 좋은 모형으로 보인다. 비선형 일반 자기회귀 조건부 이분산 과정의 경우 예측오차의 승멱(power)이 약 1.5이다. 따라서 일반 자기회귀 조건부 이분산 과정의 예측오차의 승멱인 2에 비하여 작다. 이 사실은 일반 자기회귀 조건부 이분산의 예측오차의 승멱이 과도하게 측정되고 없음을 알 수 있다. 뉴스의 비대칭성과 규모를 반영하고 있는 모형들은 한결같이 예측오차의 크기에 적절한 가중치를 부여하여 예측오차의 크기를 조정하고 있다. 이 모형의 성질과 실증분석의 결과에 의하여 예측오차의 승멱은 2 이하로 수정하여 사용해야 한다는 점이 시사되고 있다. 음의 충격이 양의 충격보다 주가의 변동성을 크게 하고 없음이 발견되었다. 주가형성에 유리한 뉴스와 불리한 뉴스가 주가의 변동성에 미치는 영향의 차이와 충격의 중대성을 양으로 표시하는 규모의 차이를 반영해주는 변수들의 추정된 계수가 미국과 일본보다 절대값에 있어서 상당히 작다. 이 현상은 뉴스의 비대칭성과 규모보다는 발생하는 충격, 즉 뉴스 자체에 보다 민감하게 반응하고 있음을 보여주고 있다. 물론 투자자들이 뉴스의 비대칭성과 규모를 완전히 무시하고 투자활동을 전개하고 있다는 것을 의미하는 것은 아니다.

  • PDF

A comparison study of Bayesian high-dimensional linear regression models (베이지안 고차원 선형 회귀분석에서의 비교연구)

  • Shin, Ju-Won;Lee, Kyoungjae
    • The Korean Journal of Applied Statistics
    • /
    • v.34 no.3
    • /
    • pp.491-505
    • /
    • 2021
  • We consider linear regression models in high-dimensional settings (p ≫ n) and compare various classes of priors. The spike and slab prior is one of the most widely used priors for Bayesian regression models, but its model space is vast, resulting in a bad performance in finite samples. As an alternative, various continuous shrinkage priors, including the horseshoe prior and its variants, have been proposed. Although each of the above priors has been investigated separately, exhaustive comparative studies of their performance have been conducted very rarely. In this study, we compare the spike and slab prior, the horseshoe prior and its variants in various simulation settings. The performance of each method is demonstrated in terms of the regression coefficient estimation and variable selection. Finally, some remarks and suggestions are given based on comprehensive simulation studies.

Multivariate Statistical Analysis and Prediction for the Flash Points of Binary Systems Using Physical Properties of Pure Substances (순수 성분의 물성 자료를 이용한 2성분계 혼합물의 인화점에 대한 다변량 통계 분석 및 예측)

  • Lee, Bom-Sock;Kim, Sung-Young
    • Journal of the Korean Institute of Gas
    • /
    • v.11 no.3
    • /
    • pp.13-18
    • /
    • 2007
  • The multivariate statistical analysis, using the multiple linear regression(MLR), have been applied to analyze and predict the flash points of binary systems. Prediction for the flash points of flammable substances is important for the examination of the fire and explosion hazards in the chemical process design. In this paper, the flash points are predicted by MLR based on the physical properties of pure substances and the experimental flash points data. The results of regression and prediction by MLR are compared with the values calculated by Raoult's law and Van Laar equation.

  • PDF

Analysis of scientific military training data using zero-inflated and Hurdle regression (영과잉 및 허들 회귀모형을 이용한 과학화 전투훈련 자료 분석)

  • Kim, Jaeoh;Bang, Sungwan;Kwon, Ojeong
    • Journal of the Korean Data and Information Science Society
    • /
    • v.28 no.6
    • /
    • pp.1511-1520
    • /
    • 2017
  • The purpose of this study is to analyze military combat training data to improve military operation and training methods and verify required military doctrine. We set the number of combat disabled enemies, which the individual combatants make using their weapons, as the response variable regarding offensive operations from scientific military training data of reinforced infantry battalion. Our response variable has more zero observations than would be allowed for by the traditional GLM such as Poisson regression. We used the zero-inflated regression and the hurdle regression for data analysis considering the over-dispersion and excessive zero observation problems. Our result can be utilized as an appropriate reference in order to verify a military doctrine for small units and analysis of various operational and tactical factors.