• 한국전기전자재료학회논문지
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• 제21권4호
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• pp.348-353
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• 2008

Most of the high voltage insulation systems, such as the power cable joint having hetero interface, are composed of more than two different insulators to improve insulating performance. The partial discharge(PD) in these hetero interface is expected to affect the total insulation performance. Thus, it is important to study electrical properties on these interfaces. This study described the influence of copper and semiconductive substance defects on $\Phi$-q-n distribution between the interface of the model cable joints to classify PD source. PD was sequentially detected for 600 cycles of the applied voltage. The K-means cluster analysis has been analyzed to investigate the $\Phi$-q-n distribution. The skewness-kurtosis(Sk-Ku) plot from K-means clustering results was defined to quantify cluster distribution and classify distribution patterns. The Sk-Ku plot is composed of skewness and kurtosis along abscissa and ordinate which indicate the asymmetry and the sharpness of distribution. As a result of the Sk-Ku plot, it was confirmed that the data was distributed in 1st 2nd and 3rd quadrant at copper foreign substance defect, but in case of semiconductive foreign substance, the data was distributed in 2nd quadrant only.

• Water Engineering Research
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• 제4권2호
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• pp.87-97
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• 2003

In this study, using the numerical model, the flow motion around skewed abutment is investigated to evaluate the skewness effect on the flow distribution. The skewness angle of the abutment which make with main flow direction is changed from $30\circ$ to $150\circ$ with increments of $10\circ$ while the contraction ratios due to the abutment are kept constant. For the investigation of the combined effects on the relationship between the skewness angle and flow intensities, this process will be .repeated fer different types of abutment (single and double) with different flow intensities. The maximum velocities and the velocity distributions, which can be obtained from each angle, are examined and analyzed corresponding to different angles of inclination. Based on successive model applications, an empirical expression, given in a function of contracted ratio and skewness angle, is derived for relating velocity amplifications according to the angle variations.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.867-873
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• 2001

In this paper we propose a family of skew- f distributions. The family is derived by a scale mixtures of skew-normal distributions introduced by Azzalini (1985) and Henze (1986). The salient features of the family are mathematical tractability and strict inclusion of the normal law. Further it includes a shape parameter, to some extent, controls the index of skewness. Necessary theory involved in deriving the family of distributions is provided and main properties of the family are also studied.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1213-1222
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• 2012

We shall derive the moment of the ratio Y/(X + Y) and the reliability P(X < Y ), and then observe the skewness of the ratio in a bivariate Pareto density function of (X, Y). And we shall consider an approximate MLE of parameters in the bivariate Pareto density function.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2004년도 학술발표논문집
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• pp.91-95
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• 2004

Moments of skew t random vectors and their quadratic forms are derived. It is shown that the moments of the sample autocovariance function and of the sample variogram estimator do not depend on a skewness parameter.

• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.901-909
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• 2013

A skewed double power function distribution is defined by a double power function distribution. We shall evaluate the coefficient of the skewness of a skewed double power function distribution. We shall obtain an approximate maximum likelihood estimator (MLE) and a moment estimator (MME) of the skew parameter in the skewed double power function distribution, and compare simulated mean squared errors for those estimators. And we shall compare simulated MSEs of two proposed reliability estimators in two independent skewed double power function distributions with different skew parameters.

• Wind and Structures
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• 제36권6호
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• pp.393-404
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• 2023

Skewness and kurtosis are important higher-order statistics for simulating non-Gaussian wind pressure series on low-rise buildings, but their predictions are less studied in comparison with those of the low order statistics as mean and rms. The distribution gradients of skewness and kurtosis on roofs are evidently higher than those of mean and rms, which increases their prediction difficulty. The conventional artificial neural networks (ANNs) used for predicting mean and rms show unsatisfactory accuracy in predicting skewness and kurtosis owing to the limited capacity of shallow learning of ANNs. In this work, the deep neural networks (DNNs) model with the ability of deep learning is introduced to predict the skewness and kurtosis on a low-rise building. For obtaining the optimal generalization of the DNNs model, the hyper parameters are automatically determined by Bayesian Optimization (BO). Moreover, for providing a benchmark for future studies on predicting higher order statistics, the data sets for training and testing the DNNs model are extracted from the internationally open NIST-UWO database, and the prediction errors of all taps are comprehensively quantified by various error metrices. The results show that the prediction accuracy in this study is apparently better than that in the literature, since the correlation coefficient between the predicted and experimental results is 0.99 and 0.75 in this paper and the literature respectively. In the untrained cornering wind direction, the distributions of skewness and kurtosis are well captured by DNNs on the whole building including the roof corner with strong non-normality, and the correlation coefficients between the predicted and experimental results are 0.99 and 0.95 for skewness and kurtosis respectively.

• 유통과학연구
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• 제20권12호
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• pp.81-87
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• 2022

Purpose: This study aims to explore the relationship between stock liquidity and skewness risk-tail risk (stock price crash risk) in an emerging market, in which problems on liquidity are more severe than in developed markets. Research design, data, and methodology: Based on the Thai market stock exchange over the period of 2000 to 2019, our sample include 13,462 firm-period observations. We employ a panel regression models regarding to five liquidity measures. These five liquidity measures cover three dimensions of liquidity namely the volume-based, price-based, and transaction cost-based measures for the liquidity-tail risk relationship. Results: We find a positively significant relationship between stock liquidity and tail risk in all cases. The finding here shows that the higher the stock liquidity, the larger the tail risk is. Conclusion: As the prior studies show inconclusive effect of stock liquidity on stock price crash risk, we demonstrate that mixed results found in prior studies are probably driven from the type of liquidity measure. The stock liquidity-tail risk association is present in the Stock Exchange of Thailand. The results remain the same regardless of the definition of tail risk and liquidity factors. An endogeneity issue is addressed by employing the two-stage least squares regression.

• Communications for Statistical Applications and Methods
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• 제11권2호
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• pp.265-274
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• 2004

The paper extends earlier work on the skew-normal distribution, a family of distributions including normal, but with extra parameter to regulate skewness. The present work introduces a singly truncated parametric family that strictly includes a truncated normal distribution, and studies its properties, with special emphasis on the relation with bivariate normal distribution.

• 대한조선학회논문집
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• 제29권2호
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• pp.1-7
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• 1992

본 연구를 통하여 극한 파고를 계산하는 방법들을 제시하였다. Type III 분포에 근거해서 분포 함수의 파라미터 산출을 위하여 non-linear multiple regression 방법, skewness 방법, maximum likelihood방법들을 사용하였다. 좀 더 정확한 결과를 얻기 위하여 추정된 분포 함수의 차이를 다항식을 도입하여 맞추었다. 제시한 방법을 응용하여 계산 예들을 보였다.