• 수산해양기술연구
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• 제57권3호
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• pp.236-245
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• 2021

In this study, a drifting test using a experimental vessel (2,966 tons) in the northern waters of Jeju was carried out for the first time in order to obtain the fundamental data for drift. During the test, it was shown that the average leeway speed and direction by GPS position were 0.362 m/s and 155.54° respectively and the leeway rate for wind speed was 8.80%. The analysis of linear regression modes about leeway speed and direction of the experimental vessel indicated that wind or current (i.e. explanatory variable) had a greater influence upon response variable (e.g. leeway speed or direction) with the speed of the wind and current rather than their directions. On the other hand, the result of multiple regression model analysis was able to predict that the direction was negative, and it was demonstrated that predicted values of leeway speed and direction using an experimental vessel is to be more influential by current than wind while the leeway speed through variance and covariance was positive. In terms of the leeway direction of the experimental vessel, the same result of the leeway speed appeared except for a possibility of the existence of multi-collinearity. Then, it can be interpreted that the explanatory variables were less descriptive in the predicted values of the leeway direction. As a result, the prediction of leeway speed and direction can be demonstrated as following equations. Ŷ₁= 0.4031-0.0032X₁+0.0631X₂-0.0010X₃+0.4110X₄ Ŷ₂= 0.4031-0.6662X₁+27.1955X₂-0.6787X₃-420.4833X₄ However, many drift tests using actual vessels and various drifting objects will provide reasonable estimations, so that they can help search and rescue fishing gears as well.

• 한국산림과학회지
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• 제98권2호
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• pp.148-155
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• 2009

The objective of this study is to know market structures of softwood logs being imported to South Korea from log producing countries. Import demand of softwood logs imported to South Korea from America, New Zealand and Chile is fixed as a function of log prices, the lagged dependent variable and output. On the basis of the adaptive expectations model, linear regression models that the explanatory variables included and the lagged dependent variable were estimated by Seemingly Unrelated Regression Equations (SURE). The short-run and long-run own price elasticity of America's softwood log import demand is -1.738 and -4.250 respectively. Then long-run elasticity is much higher than short-run elasticity. Short-run and long-run crosselasticity of New Zealand's softwood log import demand with respect to American's softwood log import price are inelastic at 0.505 and 0.883 respectively. Short-run and long-run cross-elasticity of Chile's softwood log import demands with respect to American's softwood log import prices were highly elastic at 2.442 and 4.462 respectively. Long-run elasticity was almost twice as high as short-run elasticity.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.431-434
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• 2003

In this paper we introduce a modified objective function for fuzzy c-means clustering with logistic regression model in the presence of noise cluster. The logistic regression model is commonly used to describe the effect of one or several explanatory variables on a binary response variable. In real application there is very often no sharp boundary between clusters so that fuzzy clustering is often better suited for the data.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.935-943
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• 2004

Most of the accelerated life tests deal with tests that use only one accelerating variable and no other explanatory variables. Frequently, however, there is a test to use more than one accelerating or other experimental variables, such as, for examples, a test of capacitors at higher than usual conditions of temperature and voltage, a test of circuit boards at higher than usual conditions of temperature, humidity and voltage. A accelerated life test is extended to M-level stress accelerated life test with k-stress variables. The optimal design for Weibull distribution is studied with k-stress variables.

• Communications for Statistical Applications and Methods
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• 제2권1호
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• pp.74-88
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• 1995

This article introduces a unified method of choosing the most explanatory and significant multiway partitions for classification tree design and analysis. The method is derived on the impurity reduction (IR) measure of divergence, which is proposed to extend the proportional-reduction-in-error (PRE) measure in the decision-theory context. For the method derivation, the IR measure is analyzed to characterize its statistical properties which are used to consistently handle the subjects of feature formation, feature selection, and feature deletion required in the associated classification tree construction. A numerical example is considered to illustrate the proposed approach.

• 치위생과학회지
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• 제5권4호
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• pp.171-177
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• 2005

본 연구는 어머니의 사회경제적 특성과 어머니의 구강보건지식 및 행동이 치과의료이용경험과 이용목적에 미치는 영향을 분석하고자 서울특별시에 소재한 2개의 어린이집에 내원하는 만 5-6세 유아를 자녀로 둔 103명의 어머니를 대상으로 설문조사를 실시하여 분석한 결과, 다음과 같은 결과를 얻었다. 1. 어머니의 이용목적에 따른 치과의료이용경험율은 치료(56.7%), 정기검진(23.3%), 예방(20.0%)순으로 나타났다. 2. 어머니의 사회경제적 특성 및 구강보건지식과 치과의료이용경험과의 상관성은 유의한 차이가 없었으나, 어머니의 구강보건행동과의 상관성은 치실 사용율이 낮을수록 치과의료이용경험율이 높게 나타났다(p < 0.01). 3. 어머니의 사회경제적 특성과 치과의료이용목적과의 상관성은 연령별 33-35세군(71.4%)에서, 학력별 대졸군(57.1%)에서 정기검진목적 치과의료이용경험율이 높게 나타났다(p < 0.05). 4. 어머니의 구강보건행동과 치과의료이용목적과의 상관성은 치실사용율이 높을수록 정기검진목적 치과의료이용경험율이 높게 나타났고(p < 0.001), 불소함유치약 사용율이 높을수록 치료목적 치과의료이용경험율이 높게 나타났다(p < 0.05). 5. 치과의료이용경험을 종속변수로 한 다중회귀분석 결과는 설명변량 65%로, 월평균소득(250만원 이하)이 유의미한 설명요인으로 나타났으며, 치과의료이용목적을 종속변수로 한 다중회귀분석에서는 정기검진의 경우 설명변량은 70%이였으며, 직업(전문직), 연령(33-35세)이 유의미한 설명요인으로 나타났고, 예방목적의 경우 설명변량은 78%이였으며, 연령(33-35세), 월평균소득(250만원 이하)이 유의미한 설명요인으로 나타났으며, 치료목적의 경우는 설명변량 33%이였으며, 연령(32세 이하)이 유의미한 설명요인으로 나타났다.

• 노동경제논집
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• 제38권1호
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• pp.1-30
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• 2015

한국의 구인 구직 매칭함수를 추정하였다. "사업체노동력조사"와 워크넷의 빈 일자리 수 과소 측정 문제를 극복하기 위해 채용동학모형을 통해 빈 일자리 잠재변수를 도출하고 이를 위한 도구변수를 매칭함수 추정에 활용하였다. 매칭 효율에 영향을 주는 구직자 속성과 공공고용서비스의 효과도 검증하였다. 구인 구직 매칭함수의 규모에 대한 수익불변(constant returns to scale)을 확인하였고, 매칭 효율은 구직자 중 전문대졸 학력자 비중과 정(+)의 상관관계를, 실업급여 수혜 비율과는 부(-)의 관계를 보였다.

• 통합자연과학논문집
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• 제8권1호
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• pp.56-59
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• 2015

To explore effects on each friendship, family, romance, and community in sub-variables of loneliness on academic achievement in science for Y-middle school students, multiple regression analysis is carried out by stepwise method. As the results, I found the following facts. Academic achievement in science for the students was expressed by the following equation. Academic Achievement=48.765+4.012${\times}$[Family](t=2.082, p=.039)-3.957${\times}$[Romance](t=-3.147, p=.002)+5.281${\times}$[Community](t=2.965, p=.003). And each variable value of the explanatory power affecting academic achievement in science for the students is presented in order of community (12.0%), family (6.6%), and romance (6.3%). But the friendship variable is not significant in affecting academic achievement in science.

• 한국산림과학회지
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• 제97권2호
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• pp.140-143
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• 2008

This study compared the plywood demand prediction accuracy of econometric and vector autoregressive models using Korean data. The econometric model of plywood demand was specified with three explanatory variables; own price, construction permit area, dummy. The vector autoregressive model was specified with lagged endogenous variable, own price, construction permit area and dummy. The dummy variable reflected the abrupt decrease in plywood consumption in the late 1990's. The prediction accuracy was estimated on the basis of Residual Mean Squared Error, Mean Absolute Percentage Error and Theil's Inequality Coefficient. The results showed that the plywood demand prediction can be performed more accurately by econometric model than by vector autoregressive model.

• 한국산림과학회지
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• 제95권2호
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• pp.203-208
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• 2006

This study compared the roundwood demand prediction accuracy of econometric and time-series models using Korean data. The roundwood was divided into softwood and hardwood by species. The econometric model of roundwood demand was specified with four explanatory variables; own price, substitute price, gross domestic product, dummy. The time-series model was specified with lagged endogenous variable. The dummy variable reflected the abrupt decrease in roundwood demand in the late 1990's in the case of softwood roundwood, and the boom of plywood export in the late 1970's in the case of hardwood roundwood. On the other hand, the prediction accuracy was estimated on the basis of Residual Mean Square Errors(RMSE). The results showed that the softwood roundwood demand prediction can be performed more accurately by econometric model than by time-series model. However, the hardwood roundwood demand prediction accuracy was similar in the case of using econometric and time-series model.