• Journal of Korean Society for Quality Management
• /
• v.23 no.4
• /
• pp.1-12
• /
• 1995

Sample skewness has not received much attention from researchers to design a control chart. In this paper, control charts based on two skewness measures are studied to control a manufacturing process. One skewness measure is the third central moment about mean, the other is the third L-moment which is a linear combination of order statistics. Since the exact sampling distributions of two skewness measures are unknown, empirical sampling distributions are studied using simulation. The sampling distributions are used to design control charts for skewness and performance of two skewness measures is compared.

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

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

• Communications for Statistical Applications and Methods
• /
• v.22 no.4
• /
• pp.361-375
• /
• 2015

A measure of skewness and kurtosis is proposed to test multivariate normality. It is based on an empirical standardization using the scaled residuals of the observations. First, we consider the statistics that take the skewness or the kurtosis for each coordinate of the scaled residuals. The null distributions of the statistics converge very slowly to the asymptotic distributions; therefore, we apply a transformation of the skewness or the kurtosis to univariate normality for each coordinate. Size and power are investigated through simulation; consequently, the null distributions of the statistics from the transformed ones are quite well approximated to asymptotic distributions. A simulation study also shows that the combined statistics of skewness and kurtosis have moderate sensitivity of all alternatives under study, and they might be candidates for an omnibus test.

• Journal of Advanced Marine Engineering and Technology
• /
• v.38 no.10
• /
• pp.1257-1262
• /
• 2014

The variances of atomization characteristics with the misalignment of injectors defined as the fraction of skewness for various angles of impingement and pressure conditions were studied using the doublet impinging injectors with a like-on-like arrangement. Water was used as simulant and the spray characteristics along with the changes in the skewness were analyzed using the methods of spray image photography. Experiment was carried for the impinging nozzles of orifice diameter of 1.2 mm within Reynolds numbers ranging from $9{\times}10^3-4.5{\times}10^4$ and the fraction of skewness considered for the experiment ranges from 0.0 to 0.9 at ambient temperature condition. Flat sheet with a distinct rim produced perpendicular to the plane of impinging jets goes ondisappear and sheet appears comparatively shorterwith the increase in fraction of skewness resulting the atomization of fluid droplet very close to impingement point with decrease in breakup length and increase in spray angle up to certain extent. The maximum allowable skewness was found as the result. The skewness up to the certain extent can be considered as the parameter to control the atomization characteristics of simulant inside the combustion chamberproviding the high economic performance of fuel and time.

• Wind and Structures
• /
• v.36 no.6
• /
• pp.393-404
• /
• 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.

• Water Engineering Research
• /
• v.4 no.2
• /
• pp.87-97
• /
• 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.

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

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

• Communications for Statistical Applications and Methods
• /
• v.25 no.2
• /
• pp.109-130
• /
• 2018

Several measures of multivariate skewness for scale mixtures of skew-normal distributions are derived. As a special case, those of multivariate skew-t distribution are considered in detail. Furthermore, the similarities, differences, and behavior of these measures are explored for cases of some specific members of the multivariate skew-normal and skew-t distributions using a simulation study. Since some measures are vectors, it is better to take all measures in the same scale when comparing them. In order to attain such a set of comparable indices, the sample version is considered for each of the skewness measures that are taken as test statistics for the hypothesis of t distribution against skew-t distribution. An application is reported for the data set consisting of 71 total glycerol and magnesium contents in Grignolino wine.