• 한국농공학회논문집
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• 제50권6호
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• pp.37-47
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• 2008

Photovoltaic power generation is currently being recognized as one of the most popular sources for renewable resources over the country. Although it is also being adapted to rural area for may reasons, it is important to estimate the magnitudes of power outputs with reliable statistical methodologies, while applying historical daily solar energy data, for correct feasibility analysis. In this study, one of the well-known statistical methodologies is employed to define the appropriate probability distributions for monthly power outputs for the selected rural area, county of Seo-san, province of Chungnam. The results imply that the assumption of normal distributions for several months may lead to incorrect decision-making and therefore lead to the unreliable feasibility analysis. Generalized beta and triangular distributions were found to be superior to normal distribution, when describing monthly probability distributions for daily photovoltaic power. Based on the appropriate distributions resulted from this study, Monte Carlo simulation technique was also applied to provide additional flexible information for the relevant decision makers. This study found out new finding that the probability distributions should be considered to make planning of the photovoltaic power system in rural village unit, in order to give reasonable economic analysis to the decision makers.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2003년도 추계학술대회
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• pp.49-56
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• 2003

When X and Y have independent normal distributions, we develop a Bayesian testing procedure for the equality of two coefficients of variation. Under the reference prior of the coefficient of variation, we propose a Bayesian test procedure for the equality of two coefficients of variation using fractional Bayes factor. A real data example is provided.

• Journal of the Korean Data and Information Science Society
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• 제14권4호
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• pp.1023-1030
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• 2003

When X and Y have independent normal distributions, we develop a Bayesian testing procedure for the equality of two coefficients of variation. Under the reference prior of the coefficient of variation, we propose a Bayesian test procedure for the equality of two coefficients of variation using fractional Bayes factor. A real data example is provided.

• Journal of the Korean Data and Information Science Society
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• 제21권4호
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• pp.757-764
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• 2010

In this paper, we develop the reference priors for the common location parameter in the half-normal distributions with unequal scale paramters. We derive the reference priors as noninformative prior and prove the propriety of joint posterior distribution under the general prior including the reference priors. Through the simulation study, we show that the proposed reference priors match the target coverage probabilities in a frequentist sense.

• Journal of the Korean Data and Information Science Society
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• 제22권6호
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• pp.1241-1250
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• 2011

In this paper, we develop noninformative priors for the log-normal distributions when the parameter of interest is the common mean. We developed Jeffreys' prior, th reference priors and the first order matching priors. It turns out that the reference prior and Jeffreys' prior do not satisfy a first order matching criterion, and Jeffreys' pri the reference prior and the first order matching prior are different. Some simulation study is performed and a real example is given.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.323-333
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• 2005

In this paper, we develop a MCMC method for estimating the skew normal distributions. The method utilizing the data augmentation technique gives a simple way of inferring the distribution where fully parametric frequentist approaches are not available for small to moderate sample cases. Necessary theories involved in the method and computation are provided. Two numerical examples are given to demonstrate the performance of the method.

• Communications for Statistical Applications and Methods
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• 제28권1호
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• pp.59-79
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• 2021

Value at Risk (VaR) is one of the most common risk management tools in finance. Since a portfolio of several assets, rather than one asset portfolio, is advantageous in the risk diversification for investment, VaR for a portfolio of two or more assets is often used. In such cases, multivariate distributions of asset returns are considered to calculate VaR of the corresponding portfolio. Copulas are one way of generating a multivariate distribution by identifying the dependence structure of asset returns while allowing many different marginal distributions. However, they are used mainly for bivariate distributions and are not widely used in modeling joint distributions for many variables in finance. In this study, we would like to examine the performance of various copulas for high dimensional data and several different dependence structures. This paper compares copulas such as elliptical, vine, and hierarchical copulas in computing the VaR of portfolios to find appropriate copula functions in various dependence structures among asset return distributions. In the simulation studies under various dependence structures and real data analysis, the hierarchical Clayton copula shows the best performance in the VaR calculation using four assets. For marginal distributions of single asset returns, normal inverse Gaussian distribution was used to model asset return distributions, which are generally high-peaked and heavy-tailed.

• 한국농공학회논문집
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• 제55권5호
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• pp.49-58
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• 2013

Appropriate random variables and probability density functions based on statistical analysis should be defined to execute reliability analysis. Most studies have focused on only normal distributions or assumed that the variables showing non-normal characteristics follow the normal distributions. In this study, the reliability problem with non-normal probability distribution was dealt with using the convolution method in the case that the integration domains of variables are limited to a finite range. The results were compared with the traditional method (linear transformation of normal distribution) and Monte Carlo simulation method to verify that the application was in good agreement with the characteristics of probability density functions with peak shapes. However it was observed that the reproducibility was slightly reduced down in the tail parts of density function.

• 응용통계연구
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• 제30권3호
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• pp.363-376
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• 2017

보험 시장은 포화되고 그 성장 동력은 소진되어 보험 산업이 저성장에 머물러 있는 가운데 보험사들은 치열한 경쟁 환경에 놓여있다. 이러한 상황에서 보험 상품에 대한 보험수리적 계산의 기초가 되는 보험 청구액의 흐름을 잘 설명할 수 있는 확률분포를 찾아내는 것은 중요한 쟁점이 될 것이다. 보험 청구액의 분포는 일반적으로 두꺼운 꼬리를 가지면서 왼쪽으로 치우친 로그정규분포나 파레토 분포로 잘 설명된다고 알려져 있으나 최근에는 기운 정규분포나 기운 t 분포가 보험 청구액 분포로 적절한 것으로 고찰되었다. Cooray와 Ananda (2005)는 로그정규분포와 파레토 분포의 장점을 모두 가진 로그정규-파레토 복합분포를 제시하고 단일분포보다 더 높은 적합도를 가짐을 확인하였다. 본 논문에서는 기운 정규분포와 기운 t 분포를 머리 부분으로 결합한 새로운 복합분포를 소개하고 덴마크의 화재보험 청구액 데이터와 미국의 배상 지불금 데이터에 적용하여 기존의 다른 복합분포들을 포함하여 여러 단일분포들과 그 성능을 비교한다.

• 음성과학
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• 제9권1호
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• pp.39-47
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• 2002

This paper proposes an effective method to remedy the acoustic modeling problem inherent in the usual log-normal Parallel Model Composition intended for achieving robust speech recognition. In particular, the Gaussian kernels under the prescribed log-normal PMC cannot sufficiently express the corrupted speech distributions. The proposed scheme corrects this deficiency by judiciously selecting the 'fairly' corrupted component and by re-estimating it as a mixture of two distributions using data-driven PMC. As a result, some components become merged while equal number of components split. The determination for splitting or merging is achieved by means of measuring the similarity of the corrupted speech model to those of the clean model and the noise model. The experimental results indicate that the suggested algorithm is effective in representing the corrupted speech distributions and attains consistent improvement over various SNR and noise cases.