• Proceedings of the Korean Nuclear Society Conference
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• 1999.05a
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• pp.75-75
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• 1999

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.481-504
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• 2006

VaR, a tail-related risk measure is now widely used as a tool for a measurement and a management of financial risks. For more accurate measurement of VaR, recently we are particularly concerned about the approach based on extreme value theory rather than the traditional method based on the assumption of normal distribution. However, many studies about the approaches using extreme value theory was done only for the univariate case. In this paper, we discuss portfolio risk measurements with modelling multivariate extreme value distributions by combining copulas and extreme value theory. We also discuss the estimation of ES together with VaR as portfolio risk measures. Finally, we investigate the relative superiority of EVT-copula approach than variance-covariance method through the back-testing of an empirical data.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.395-407
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• 2016

This study aims to apply the G-theory for estimation of reliability of evaluation scores between raters on Taekwondo Poomsae rating categories. Selecting a number of game days and raters as multiple error sources, we analyzed the error sources caused by relative magnitude of error variances of interaction between the factors and proceeded with D-study based on the results of G-study for optimal determination of measurement condition. The results showed below. The estimated outcomes of variance component for accuracy among the Taekwondo Poomsae categories with G-theory showed that impact of error was the biggest influence factor in raters conditions and in order of interaction in subjects and between subjects, also impact of variance component estimation error on expression category was the major influence factor in interaction and in order of the between subjects and raters. Finally, the result of generalizability coefficient estimation via D-study showed that measurement condition of optimal level depend on the number of raters was 8 persons of raters on accuracy category, and stable reliability on expression category was gained when the raters were 7 persons.

• Journal of the Korean GEO-environmental Society
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• v.6 no.3
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• pp.25-34
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• 2005

The governing design point of shallow foundation is not its bearing capacity but its settlemen and N-value by the SPT is one of the key parameters for settlement estimation. However, if the N-value is more than 50/30, such as 50/10 or 50/20, the N-vlaues are not blow count of 30cm depth penetration. In these cases, the estimated settlements have big difference with the measured values because the applied maximum N value for the settlement estimation is 50. Therefore, in this study, the modified method for N-value estimation is suggested. The settlements by four methods, which are based on Elastic Theory with application of modified N-value, are compared with the Origina Plate Load Test data. The same comparision was carried out with another seven Empirical Methods. The result of this study showed that the error range of settlement is decreased from 260.4~2136.5% to 20.3~272.7%. Among four methods which are based on Elastic Theory, the original method by Elastic Theory is the most accurate with the application of modified N-value. Among Empirical Methods, Terzaghi-Peck's(1948, 1967) modified method 1 is the most accurate with the application of modified N-value. The differences between the original method by Elastic Theory and Terzaghi-Peck's(1948, 1967) modified method 1 are neglectable.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6799-6806
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• 2015

Electric energy consumption is always followed by the introduction of diversity scale-up and state-of-the-art equipments in logistic centers. In order to analyze the status and the characteristic of the electric energy consumption quantitatively, and also to evaluate the efficiency of the electric energy, this research aims to develop an estimation model of standard electric energy consumption for logistic centers. The proposed model applies the thermodynamics theory so as to effectively reflect the peculiarity that the temperature in the logistic center influences the electric energy consumption. And the model consists of the energy consumed by the refrigerator, which can be subdivided into the heat conducted through the wall, the heat convected by the open doors and the heat lost into the goods, and the electric consumption of the machinery equipments. The model also includes a variety of explanatory variables to support an operator of logistics centers in evaluating the efficiency of energy consumption and establishing improvement strategies for energy efficiency. Application of the model developed in this study is discussed with observed data on energy consumption of a logistics center.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.1
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• pp.201-216
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• 2013

Diffusion is a basic mathematical tool for modern financial engineering. The theory of the estimation methods for diffusion models is an important topic of the financial engineering. Many researches have been tried to apply the likelihood estimation method for estimating diffusion models. However, the likelihood estimation method for diffusion is complicated and needs much amount of computing. In this paper we develop the estimation methods which are simple enough to be compared to the Euler approximation method, and efficient enough statistically to be compared to the likelihood estimation method. We devise pseudo-likelihood and propose the maximum pseudo-likelihood estimation methods. The pseudo-likelihoods are obtained by approximating the transition density with normal distributions. The means and the variances of the distributions are obtained from the delta expansion suggested by Lee, Song and Lee (2012). We compare the newly suggested estimators with other existing estimators by simulation study. From the simulation study we find the maximum pseudo-likelihood estimator has very similar properties with the maximum likelihood estimator. Also the maximum pseudo-likelihood estimator is easy to apply to general diffusion models, and can be obtained by simple numerical steps.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.431-438
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• 2004

This study is on control-gain estimation of energy dissipation control algorithms. Velocity feedback, bang-bang, and energy dissipation control algorithms are proposed based on the Lyapunov stability theory and their performances are evaluated and compared. Saturation problem is considered in the design of the velocity feedback and energy dissipation control algorithms, and chattering problem in bang-bang control is solved by using boundary layer. Numerical results show that the proposed control algorithms can dissipate the structural energy induced by wind loads efficiently, and thus provide good control performance.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.657-667
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• 2006

The concept of entropy, introduced in communication theory by Shannon (1948) as a measure of uncertainty, is of prime interest in information-theoretic statistics. This paper considers the minimum variance unbiased estimation for the maximum entropy of the transformed inverse Gaussian random variable by $Y=X^{-1/2}$. The properties of the derived UMVU estimator is investigated.

• Journal of Biosystems Engineering
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• v.9 no.1
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• pp.5-10
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• 1984

Using the renewal theory based on the Weibull distribution, an estimation was made on the number of replacement parts annually required for the after-service of some major parts of power tiller at the local repair shops or dealers. The production requirements of the parts were also estimated for the service in the next 5 years following the sales of power tillers.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.13-20
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• 1994

The spectrum estimation methods of random processes are expressed in this paper. Beginning with the basic theory, non-parametric and parametric methods are overviewed. As to non-parametric method, numerical calculation method is also discussed. As to parametric method, AR model is a very famous and effective model representing random process. Estimation methods of AR parameters which have been proposed are mentioned here. Wavelet analysis is a recently interested technique in signal processing. An application of wavelet analysis is also shown.