• Communications for Statistical Applications and Methods
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• v.20 no.5
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• pp.395-404
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• 2013

This paper studies the skewness of the absolute value GARCH(1, 1) models with Gaussian mixture innovations (Gaussian mixture AVGARCH(1, 1) models). The maximum estimated-likelihood estimator (MELE) employed (a two- step estimation method in order to estimate the skewness of Gaussian mixture AVGARCH(1, 1) models. Through the real data analysis, the adequacy of adopting Gaussian mixture innovations is exhibited in reflecting the skewness of two major Korean stock indices.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.819-822
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• 2002

It is necessary for the numerical simulation of 3-dimensional incompressible isotropic decaying turbulence to construct 3-dimensional initial velocity field which resembles the fully developed turbulence. Although the previous velocity field generation method proposed by Rogallo(1981) satisfies continuity equation and 3-dimensional energy spectrum, it has limitation, as indicated in his paper, that it does not produce the higher velocity moments(e. g. velocity derivative skewness) characteristic of real turbulence. In this study, a new velocity field generation method which is able to control velocity derivative skewness of initial velocity field is proposed. Brief descriptions of the new method and a few parameters which is used to control velocity derivative skewness are given. A large eddy simulation(LES) of isotropic decaying turbulence using dynamic subgrid-scale model is carried out to evaluate the performance of the initial velocity field generated by the new method. It was shown that the resolved turbulent kinetic energy decay curve and the resolved enstrophy decay curve from the initial field of new method were more realistic than those from the initial field of Rogallo's method. It was found that the dynamic model coefficient from the former was initially half the stationary value and experienced relatively short transition period, though that from the latter was initially zero and experienced relatively longer transition period.

• Journal of the Korea Safety Management & Science
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• v.9 no.2
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• pp.215-233
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• 2007

Even though the ad hoc Shewhart methods remain controversial due to various mathematical flaws, there is little disagreement among researchers and practitioners when a set of process data has a skewness distribution. In the context and language of process control, the error related to the process data shows that time to signal increases when a control parameter shifts to a skewness direction. In real-world industrial settings, however, quality practitioners often need to consider a skewness distribution. To address this situation, we developed an enhanced design method to utilize advantages of the traditional attribute control chart and to overcome its associated shortcomings. The proposed design method minimizes bias, i.e., an average time to signal for the shift of process from the target value (ATS) curve, as well as it applies a variable sampling interval (VSI) method to an attribute control chart for detecting a process shift efficiently. The results of the factorial experiment obtained by various parameter circumstances show that the VSI c control chart using nearly unbiased ATS design provides the smallest decreasing rate in ATS among other charts for all experimental cases.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.03b
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• pp.30.1-33
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• 1999

Finite element simulation with experimental analysis of Taguchi's orthogonal array was carried out to know the effects of material and forming parameters on the cup earing and skewness. It was revealed that the planar anisotropy was the most influencing factor in the cup ear formation whereas blank holding force and material properties such as strength and thickness deviation at the coil edge had a relatively high effect on the cup skewness.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.663-675
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• 2023

Purpose: Skewness is an indicator used to measure the asymmetry of data distribution. In the past, product quality was judged only by mean and variance, but in modern management and manufacturing environments, various factors and volatility must be considered. Therefore, skewness helps accurately understand the shape of data distribution and identify outliers or problems, and skewness can be utilized from this new perspective. Therefore, we would like to propose a statistical quality control method using skewness. Methods: In order to generate data with the same mean and variance but different skewness, data was generated using normal distribution and gamma distribution. Using Minitab 18, we created 20 sets of 1,000 random data of normal distribution and gamma distribution. Using this data, it was proven that the process state can be sensitively identified by using skewness. Results: As a result of the analysis of this study, if the skewness is within ± 0.2, there is no difference in judgment from management based on the probability of errors that can be made in the management state as discussed in quality control. However, if the skewness exceeds ±0.2, the control chart considering only the standard deviation determines that it is in control, but it can be seen that the data is out of control. Conclusion: By using skewness in process management, the ability to evaluate data quality is improved and the ability to detect abnormal signals is excellent. By using this, process improvement and process non-sub-stitutability issues can be quickly identified and improved.

• Water Engineering Research
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• v.4 no.2
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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.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.9
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• pp.1148-1156
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• 2000

The QUICK scheme for convection terms is modified for unstructured finite volume method by using linear reconstruction technique and validated through the computation of two well defined laminar flows. It uses two upstream grid points and one downstream grid point in approximating the convection terms. The most upstream grid point is generated by considering both the direction of flow and local grid line. Its value is calculated from surrounding grid points by using a linear construction method. Numerical error by the modified QUICK scheme is shown to decrease about 2.5 times faster than first order upwind scheme as grid size decreases. Computations are also carried out to see effects of the skewness and irregularity of grid on numerical solution. All numerical solutions show that the modified QUICK scheme is insensitive to both the skewness and irregularity of grid in terms of the accuracy of solution.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.239-239
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• 2015

This study presents a bivariate extension of the goodness-of-fit measure for regional frequency distributions developed by Hosking and Wallis [1993] for use with the method of L-moments. Utilising the approximate joint normal distribution of the regional L-skewness and L-kurtosis, a graphical representation of the confidence region on the L-moment diagram can be constructed as an ellipsoid. Candidate distributions can then be accepted where the corresponding the oretical relationship between the L-skewness and L-kurtosis intersects the confidence region, and the chosen distribution would be the one that minimises the Mahalanobis distance measure. Based on a set of Monte Carlo simulations it is demonstrated that the new bivariate measure generally selects the true population distribution more frequently than the original method. An R-code implementation of the method is available for download free-of-charge from the GitHub code depository and will be demonstrated on a case study of annual maximum series of peak flow data from a homogeneous region in Italy.

• The Mathematical Education
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• v.42 no.3
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• pp.419-423
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• 2003

The main purpose of this paper is to investigate effects of skewness and kurtosis on the one-sample test. We have found that type I error brought about a little bit change which is ignorable in relation to kurtosis. Also the change of type I error was completely based on skewness under the same size of the sample. We conclude that using t-test is more similar to robust than using z-test. In introductory statistics classes where data analysis includes techniques for detecting skewness, we recommend the t-test when skewness is smaller than the value 1 to the one-sample test for a mean when the variances is unknown using the probability of a type I error as the criterion of interest.

• Journal of Korea Water Resources Association
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• v.35 no.3
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• pp.275-284
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• 2002

In this study, a method of random resampling of residuals from stochastic models such as the Monte-Carlo model, the lag-one autoregressive model(AR(1)) and the periodic lag-one autoregressive model(PAR(1)), has been adopted to generate a large number of long traces of annual and monthly steamflows. Main advantage of this resampling scheme called the Bootstrap method is that it does not rely on the assumption of population distribution. The Bootstrap is a method for estimating the statistical distribution by resampling the data. When the data are a random sample from a distribution, the Bootstrap method can be implemented (among other ways) by sampling the data randomly with replacement. This procedure has been applied to the Yongdam site to check the performance of Bootstrap method for the streamflow generation. and then the statistics between the historical and generated streamflows have been computed and compared. It has been shown that both the conventional and Bootstrap methods for the generation reproduce fairly well the mean, standard deviation, and serial correlation, but the Bootstrap technique reproduces the skewness better than the conventional ones. Thus, it has been noted that the Bootstrap method might be more appropriate for the preservation of skewness.