• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.995-1005
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• 2009

Conditional correlation between financial time series plays an important role in risk management, asset allocation and portfolio selection and therefore diverse efforts for modeling conditional correlations in multivariate-GARCH processes have been made in last two decades. In particular, CCC (cf. Bollerslev, 1990) and DCC(dynamic conditional correlation, cf. Engle, 2002) models have been commonly used since they are relatively parsimonious in the number of parameters involved. This article is concerned with DCC modeling for multivariate GARCH processes in comparison with CCC specification. Various multivariate financial time series are analysed to illustrate possible advantages of DCC over CCC modeling.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.19-33
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• 2008

Linear regression method, proposed by Haseman and Elston(1972), for detecting linkage to a quantitative trait of sib pairs is a linkage testing method for a single locus and a single trait. However, multivariate methods for detecting linkage are needed, when information from each of several traits that are affected by the same major gene are available on each individual. Amos et al. (1990) extended the regression method of Haseman and Elston(1972) to incorporate observations of two or more traits by estimating the principal component linear function that results in the strongest correlation between the squared pair differences in the trait measurements and identity by descent at a marker locus. But, it is impossible to control the probability of type I errors with this method at present, since the exact distribution of the statistic that they use is yet unknown. In this paper, we propose a multivariate nonparametric trend test for detecting linkage to multiple traits. We compared with a simulation study the efficiencies of multivariate nonparametric trend test with those of the method developed by Amos et al. (1990) for quantitative traits data. For multivariate nonparametric trend test, the results of the simulation study reveal that the Type I error rates are close to the predetermined significance levels, and have in general high powers.

• Journal of Korean Society of Forest Science
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• v.86 no.1
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• pp.9-16
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• 1997

The contingent valuation method(CVM) has been used to evaluate the economic value of nonmarket goods such as forest recreation. There are two commonly used CVM questionnaire formats: open-ended and closed-ended. This study evaluates the net economic value associated with day use downhill skiing, using CVM. A random, on-site survey of skiers in Muju, Korea generated the value estimates. In this paper a nonparametric test is introduced to find whether the difference between value estimates from open-ended and closed-ended formats are significantly different because the distributions of WTPs are non-normally distributed. The results show that the net economic benefits of a skier in Muju varies from \15,131 to \25,332. The closed-ended values were 1.15 to 1.67 times as large as the open-ended values, depending on the model specifications. In nonparametric test the mean WTPs of the open-ended and close-ended applications are significantly different. Its reason may be that closed-ended can be more reducing the incentive for strategic behavior than open-ended question. However, we cannot conclude that the closed-ended method is superior to the open-ended method.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1029-1038
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• 2014

Bayesian experimental design is a useful concept in applied statistics for the design of efficient experiments especially if prior knowledge in the experiment is available. However, a theoretical or numerical approach is not simple to implement. We review the concept of a Bayesian experiment approach for linear and nonlinear statistical models. We investigate relationships between prior knowledge and optimal design to identify Bayesian experimental design process characteristics. A balanced design is important if we do not have prior knowledge; however, prior knowledge is important in design and expert opinions should reflect an efficient analysis. Care should be taken if we set a small sample size with a vague improper prior since both Bayesian design and non-Bayesian design provide incorrect solutions.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.17-26
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• 2004

항공운송산업에서 항공화물이 차지하는 비중이 점차적으로 확대되고 있으며 향후 2020년(보잉은 2022년)까지의 성장률도 보잉과 에어버스에서는 여객 수요보다 화물수요가 각 1.3%, 0.8%의 높은 성장을 거둘 것이라는 전망을 하고 있다. 특히 에어버스에서는 아시아 태평양 지역 역내와 중국 발 유럽행의 항공화물이 평균 7.0%의 높은 성장을 할 것으로 전망하고 있다. 이러한 높은 성장 전망 외에도 항공화물이 항공운송산업 혹은 세계경제의 선행지표로도 사용되고 있다. 이렇듯 항공운송산업에서 항공화물 부문의 역할이 점차적으로 증대되고 있어 본 연구에서는 항공화물 사업부문에 많은 활동을 하고 있는 항공사의 효율성이 그렇지 않은 항공사의 효율성을 비교하는 연구를 하였다. 먼저 항공 화물 매출액 기준 상위 10개사(2002년 기준)의 효율성을 자료포락 분석(DEA, Data Envelopment Analysis)을 이용 분석하였다. 그리고 이를 이용하여 항공사 전체 매출액 상위 10개사(화물 매출액 상위 10개사를 제외), 미국의 9개 항공사(상위 50대 항공사 중), 기타 10개사를 선정하여 각각의 효율성 비교를 통하여 항공화물 사업을 활발히 하는 항공사와 그렇지 않은 항공사와의 효율성에 대해 상대적 비교를 하였다. 이를 통해 항공화물 사업 부문이 항공사의 경영 효율성에 미치는 영향에 대해 간접 비교를 시도하였다. 분석 결과 항공운송사업중 항공화물 부문이 상위 10대 항공사 효율성이 다른 그룹의 항공사 보다 높게 제시되었다. 이는 항공사의 운송 사업을 화물 운송과 여객 운송 부문의 공동 네트워크의 활용을 통한 시너지 효과를 통해 항공사 효율성을 높일 수 있음을 의미한다.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.103-114
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• 2014

Data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) with multiple performance factors that are grouped into outputs and inputs. DEA has proven to be superior to simple aggregation of performance measures, and is also useful for evaluating the performance of construction companies for comparison with competitor performance. The purpose of this study was to survey literatures on the application of DEA methodology and to propose a methodological scheme to measure the performance of construction organizations. Articles on previous studies were surveyed and examined as part of a comprehensive review. The survey revealed that the application of DEA in the construction industry was li mited. Further, the survey indicated that there is a need for the development of a methodological framework on the special goals and subjects of performance measurement, methods of data structure and collection, selection of appropriate DEA models, analysis of results, and post-test. Based on the survey, this study identified and discussed the types of major issues and topics for future studies from a methodological perspective, which could be helpful to researchers interested in using DEA to study performance issues in construction organizations.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.275-287
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• 1998

The goal of this paper is to suggest the goodness-of-fit test statistic for the no effect model. The comparisons of powers on test statistics are conducted with three types alternative modles.

• Environmental and Resource Economics Review
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• v.11 no.3
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• pp.447-463
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• 2002

The heat demand prediction is an essential issue in management of district heating system. Without an accurate prediction through the lead-time period, it might be impossible to make a rational decision on many issues such as heat production scheduling and heat exchange among the plants which are very critical for the district heating company. The heat demand varies with the temperature as well as the time nonlinearly. And the parametric specification of the heat demand model would cause a misspecification bias in prediction. A nonparametric model for the short-term heat demand prediction has been developed as an alternative to avoiding the misspecification error and tested with the actual data. The prediction errors are reasonably small enough to use the model to predict a few hour ahead heat demand.

• Journal of the Korean Data and Information Science Society
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• v.11 no.2
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• pp.235-245
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• 2000

In this paper, we consider the Regression Quantiles Estimators in nonlinear regression models. This paper provides the sufficient conditions for strong consistency and asymptotic normality of proposed estimation and drives asymptotic relative efficiency of proposed estimatiors with least square estimation. We give some examples and results of Monte Carlo simulation to compare least square and regression quantile estimators.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.849-856
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• 2011

In this paper, we study the influence analysis of admission and enrollment variables including individual characteristics variables on employment of graduate students at K university. First, logistic regression analysis is used to examine the main effects of admission, enrollment variables including student's individual characteristics on employment. Also, decision tree analysis is used to examine the interaction effects for the variables on employment. The results of this paper may be helpful to K university in designing effective job finding strategies for graduate students.