• Tunnel and Underground Space
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• v.22 no.2
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• pp.120-129
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• 2012

Recently, mining facilities have being installed in an underground space according to a social demand for environment-friendly mine development. The underground structures for mining facilities usually requires a large volume of space with width greater than height, and thus the stability assessment of the large-scale underground mine structure is an important issue. In this study, we analysed a factor of safety based on strength reduction method, and proposed a numerical design approach to determining the dimension of underground mine structures in combination with a strength reduction method and a multivariate regression analysis. Input design parameters considered in the present study were the stress ratio and shear strength of rock mass, and the width and cover depth of underground mine structures. The stabilities of underground mine structures were assessed in terms of factor of safety under different conditions of the above input parameters. It was calculated by the strength reduction method, and several kinds of fit functions were obtained through various multivariate regression analyses. Using a best-fit regression model, we proposed the charts which provide preliminary design information on the dimension of underground mine structures.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1845-1849
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• 2006

본 연구에서는 관측자료에 나타난 Clark 단위도의 매개변수를 검토하고 그 변동성을 평가하였다. 강우-유출과정에 영향을 미치는 유역 및 기상 특성인자들을 확률밀도함수로 정량화하였고, 유역의 집중시간 및 저류상수를 호우사상의 특성 및 유역의 조건을 고려하여 다변량 회귀분석을 실시하였다. 이를 Monte Carlo 모의기법에 적용하여 유역평균 저류상수 및 집중시간에 대한 신뢰구간을 추정하였다. 또한 신뢰구간을 좁히기 위한 방안으로 관측된 집중시간 및 저류상수를 Bootstrap 기법으로 처리하였다. 그 결과 유역을 대표하는 유출특성의 결정에는 관측 강우-유출사상의 수가 어느 정도 확보된다고 하더라도 여전히 높은 불확실성을 피하기 힘들다는 것이다. 집중시간의 경우는 그 분포가 상당히 왜곡된 형태여서 단순한 산술평균은 상당히 왜곡된 추정치를 제시할 가능성이 높다. 단순히 관측치를 이용한 경우보다 Monte Carlo 모의기법에 의한 경우 신뢰구간이 2-3배정도 좁게 나타났다. 어느 정도 신뢰도 있는 집중시간 및 저류상수의 추정을 위해서는 최소 10여개 대략 20개 정도 이상의 호우사상이 필요할 것으로 판단된다. 본 연구의 목적은 주어진 유역을 대표할 수 있는 집중시간 및 저류상수를 결정하고자 하는 것이다. 따라서 본 연구에서의 방법론을 적용하여 관측자료가 존재하는 다양한 유역에서의 집중시간 및 저류상수를 결정하고, 이를 지형인자 유역특성을 고려하여 회귀분석하는 경우 보다 정도 있는 경험식의 개발도 가능할 것이다.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.321-328
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• 2009

In regression analysis, the ordinary least squares estimates of regression coefficients become poor, when the correlations among predictor variables are high. This phenomenon, which is called multicollinearity, causes serious problems in actual data analysis. To overcome this multicollinearity, many methods have been proposed. Ridge regression, shrinkage estimators and methods based on principal component analysis (PCA) such as principal component regression (PCR) and latent root regression (LRR). In the last decade, many statisticians discussed sensitivity analysis (SA) in ordinary multiple regression and same topic in PCR, LRR and logistic principal component regression (LPCR). In those methods PCA plays important role. Many statisticians discussed SA in PCA and related multivariate methods. We introduce the method of PCR and LRR. We also introduce the methods of SA in PCR and LRR, and discuss the properties of SA in PCR and LRR.

• Journal of Korea Port Economic Association
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• v.35 no.3
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• pp.61-72
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• 2019

In order to enhance the competitiveness of the container shipping industry and promote its development, based on the empirical analyses using multivariate time series models, this study aims to suggest a few strategies related to the dynamics of the container shipping market. It uses the vector autoregressive (VAR) and vector error correction (VEC) models as analytical methodologies. Additionally, it uses the annual trade volumes, fleets, and freight rates as the dataset. According to the empirical results, we can infer that the most exogenous variable, the trade volume, exerted the highest influence on the total dynamics of the container shipping market. Based on these empirical results, this study suggests some implications for ship investment, freight rate forecasting, and the strategies of shipping firms. Concerning ship investment, since the exogenous trade volume variable contributes most to the uncertainty of freight rates, corporate finance can be considered more appropriate for container ship investment than project finance. Concerning the freight rate forecasting, the VAR and VEC models use the past information and the cointegrating regression model assumes future information, and hence the former models are found better than the latter model. Finally, concerning the strategies of shipping firms, this study recommends the use of cycle-linked repayment scheme and services contract.

• The Korean Journal of Financial Studies
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• v.5 no.1
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• pp.135-164
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• 1999

본(本) 연구(硏究)는 Jobson(1982)의 주식(株式)의 수익율(收益率)이 정규분포(正規分布)를 할 경우에 다변량(多變量)의 통계학(統計學)을 이용하여 CAPM과 APM을 검증(檢證)하는 방법(方法)을 유도하였다. 이에따라 회귀분석(回歸分析)에 의한 검증방법(檢證方法)과 다변량(多變量)의 검증방법(檢證方法)을 제시하고 현실적으로 CAPM과 APM이 한국증권시장(韓國證券市場)에서 적용가능(適用可能)한가에 대한 실증적(實證的) 검증(檢證)을 실시하였다. 실증적(實證的) 검증(檢證)을 위하여 먼저 우리나라의 주식수익율자료(株式收益率資料)를 1980년 1월부터 1997년 6월까지의 월별자료(月別資料)에 의하여 11개 산업별(産業別) 분류작업을 통하여 산업별(産業別)포트폴리오를 구성하였다. 특히 APM의 경우에는 요인(要因)의 증가에 따라 APM이 한국증권시장에서 적용가능한가를 검증(檢證)하기 위하여 요인(要因)을 2개, 6개 그리고 10개까지 증가시켜 모형(模型)의 적합성(適合性)을 검증(檢證)하였다. 검증결과(檢證結果), CAPM과 APM모두 한국증권시장(韓國證券市場)에서 적용가능(適用可能)한 것으로 나타났다. 특히 APM의 경우에는 요인(要因)이 2개, 6개와 10개로 증가시 어떤 경우에도 적용가능한 것으로 나타났다. 이는 기대수익율(期待收益率)의 설명력을 높이기 위하여 몇 개의 가격화(價格化) 요인(要因)이 APM에 영향을 미치는 가를 연구하는 전통적인 검증방법(檢證方法)은 큰 의미가 없는 것으로 나타났다.

• Journal of Navigation and Port Research
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• v.28 no.8
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• pp.687-697
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• 2004

This paper is aimed to guide ocean-going companies to reasonable decisions and to increase the competitiveness of Korean shipping industry by clarifying the determinants of political costs of ocean-going companies, which only depend for the enormous amount of money to introduce the operating fixed assets, or the vessels, upon the supporting policy from the government or the loan from the related financial institutions. As independent variables of the political costs, 5 elements were settled such as company size(sales, total assets and market share), debit ratio, capital concentration ratio, profitability(operating profit) and marine risk(sales fluctuation). To verify the relations and the effect level between dependent variables and political costs, the Multiple Regression Analysis Model was applied The result of the analysis shows significantly positive relations between size variables and political cost of shipping industry. Moreover, debt ratio and profitability were proved significant related with political costs of shipping industry.

• Journal of Korean society of Dental Hygiene
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• v.21 no.5
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• pp.535-543
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• 2021

Objectives: This study investigated the relationship between the Korean healthy eating index (KHEI) and periodontal disease in the Korean adult population. Methods: The data used in the analyses were obtained from the seventh Korean National Health and Nutrition Examination Survey (2016-2018). Data were analyzed by chi-square tests and t-test. Multiple regression analysis was also performed to assess the association between KHEI and periodontal disease. Statistical significance was set at p<0.05. Results: Multiple logistic regression analysis adjusted for socioeconomic variables showed that medical and health behavior variables were significantly related to the KHEI 1 (<63.7, odds ratio [OR]: 1.23, 95% confidence interval [CI]: 1.03-1.46), KHEI 2 (63.7-79.9, OR: 1.14, 95% CI: 0.97-1.34), and risk for periodontal disease. Conclusions: The results showed a significant association between the KHEI and periodontal disease in the Korean adult population.

• Information Systems Review
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• v.22 no.1
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• pp.73-89
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• 2020

This study started to identify the "Forward-looking" of the technology appraisal model introduced to diversify financing methods of SMEs and improve financial accessibility. The multivariate regression analysis was performed by setting the business performance(growth, profitability, and stability) of technology financing companies as dependent variables, technology appraisal items as independent variables, number of employees, age of the company, asset and the Korea Standard of Industry Classification related to firm size and industry characteristics as control variables. As a result of the analysis, the technology appraisal items did not explain the profitability of the company significantly and had a limited explanatory power on growth potential. However, in terms of stability, we confirmed that R&D capacity is a significant variable explaining the debt ratio of technology financing companies. Therefore, it is concluded that the 'Forward-looking' reflection on the growth and profitability of the company should be strengthened in the future adjustment of the technology appraisal model and the development of the technology appraisal model for investment.

• Journal of Korean Tunnelling and Underground Space Association
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• v.2 no.2
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• pp.41-49
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• 2000

Rock Mass Rating has been widely applied to the underground tunnel excavation and many other practical problems in rock engineering. However, Rock Mass Rating is hard, even by the experts of tunnel assessment owing to lack of investigation system. In this study, using multivariate analysis we presented rock mass rating system that is objective and easy to use. The constituents of RMR are decided to RQD, condition of discontinuities, groundwater conditions, intact rock strength, orientation of discontinuities, spacing of discontinuities in important order. In each step, we proposed the best multiple regression model for RMR system.

• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.31-38
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• 2000

Relationships between hydrologic variables are often nonlinear. Usually the functional form of such a relationship is not known a priori. A multivariate, nonparametric regression methodology is provided here for approximating the underlying regression function using locally weighted polynomials. Locally weighted polynomials consider the approximation of the target function through a Taylor series expansion of the function in the neighborhood of the point of estimate. The utility of this nonparametric regression approach is demonstrated through an application to nonparametric short term forecasts of the biweekly Great Salt Lake volume.volume.