• 제목/요약/키워드: skewness distribution

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통계적 품질관리를 위한 왜도의 활용 (Utilization of Skewness for Statistical Quality Control)

  • 김훈태;임성욱
    • 품질경영학회지
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    • 제51권4호
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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.

추진장약 수락시험시 포구속도 확률분포에 기준탄이 미치는 영향 (Effects of Calibration Rounds on the Statistical Distribution of Muzzle Velocity in Acceptance Test of Propelling Charge)

  • 박성호;김재훈
    • 한국군사과학기술학회지
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    • 제17권2호
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    • pp.204-212
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    • 2014
  • The purpose of this paper is to investigate the effects of calibration rounds on the statistical distribution of the muzzle velocity in acceptance test of propelling charge. It is shown that the normal distribution fits best among statistical distributions from goodness-of fit test. The 3p-Weibull distribution is also acceptable because the shape of the probability density function curve is similar to that of normal distribution and it also has near zero skewness value. Muzzle velocities of test rounds uncompensated by calibration rounds showed high variation and had comparatively higher skewness. Because the skewness of normal distribution is defined to be zero, calibration rounds make the normality of data higher.

Power t distribution

  • Zhao, Jun;Kim, Hyoung-Moon
    • Communications for Statistical Applications and Methods
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    • 제23권4호
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    • pp.321-334
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    • 2016
  • In this paper, we propose power t distribution based on t distribution. We also study the properties of and inferences for power t model in order to solve the problem of real data showing both skewness and heavy tails. The comparison of skew t and power t distributions is based on density plots, skewness and kurtosis. Note that, at the given degree of freedom, the kurtosis's range of the power t model surpasses that of the skew t model at all times. We draw inferences for two parameters of the power t distribution and four parameters of the location-scale extension of power t distribution via maximum likelihood. The Fisher information matrix derived is nonsingular on the whole parametric space; in addition we obtain the profile log-likelihood functions on two parameters. The response plots for different sample sizes provide strong evidence for the estimators' existence and unicity. An application of the power t distribution suggests that the model can be very useful for real data.

Multivariate measures of skewness for the scale mixtures of skew-normal distributions

  • Kim, Hyoung-Moon;Zhao, Jun
    • Communications for Statistical Applications and Methods
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    • 제25권2호
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    • pp.109-130
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    • 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.

가변추출간격을 이용한 c 관리도의 최적설계 (Optimal Design of c Control Chart using Variable Sampling Interval)

  • 박주영
    • 대한안전경영과학회지
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    • 제9권2호
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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.

한국 KOSPI시장의 GARCH-VaR 측정모형 및 분포간 성과평가에 관한 연구:롱 및 숏 포지션 전략을 중심으로 (Comparing Among GARCH-VaR Models and Distributions from Korean Stock Market (KOSPI) :Focusing on Long and Short Positions)

  • 손판도
    • 재무관리연구
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    • 제25권4호
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    • pp.79-116
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    • 2008
  • 본 논문은 1980년 1월부터 2004년 9월까지 한국 거래소 시장수익률을 이용하여 RiskMetrics, GARCH, IGARCH, GJR, APARCH 등의 모형에 정규분포, 스튜던트 t분포, 왜도 스튜던트 t분포 등을 이용하여 어느 분포를 가진 모형이 보다 더 정확한 VaR을 추정할 수 있는지를 실증검증 하였다. 실증결과 표본 내 검증 시 모든 신뢰수준($90%{\sim}99.9%$)에서 롱 포지션 전략에서는 ${\lambda}=0.87$를 가진 IGARCH 모형 및 왜도 스튜던트 t분포가 가장 우월하며, 숏 포지션 전략에서는 GARCH 및 GJR 모형이 그리고 왜도 스튜던트 t분포가 가장 우월하였고, 99% 이상의 신뢰수준에서는 또한 ${\lambda}=0.87$를 가진 IGARCH 모형이 롱 및 숏 포지션 양 전략에서 우월하였다. 또한 분포의 경우 롱 포지션에서 왜도 스튜던트 t분포, 숏 포지션에서 스튜던트 t분포가 가장 우월하였다. 표본 외 검증에서도 동일한 결과를 제시하고 있다.

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EM 알고리즘에 의한 다변량 치우친 정규분포 혼합모형의 근사적 적합 (An approximate fitting for mixture of multivariate skew normal distribution via EM algorithm)

  • 김승구
    • 응용통계연구
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    • 제29권3호
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    • pp.513-523
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    • 2016
  • 다중 치우침 모수벡터를 가진 다변량 치우친 정규분포 (MSNMix)를 EM 알고리즘으로 적합하려면 E-step에서 다변량 절단 정규분포의 적률과 확률을 계산해야 하는데 이것은 매우 큰 계산 시간을 요구한다. 그래서 비대칭 자료를 적합하는데 흔히 단순 치우침 모수를 가진 모형을 적용한다. 이 모형은 단변량 처리방식으로 적합하는 것이 가능하기 때문에 처리속도가 매우 빠르다. 그러나 단순 치우침 모수를 적용하는 것은 응용에서 비현실적인 경우가 많다. 본 논문에서는 다중 치우침 모수를 가지는 MSNMix의 근사적 추정법을 제안하는데, 이 방법은 단변량 처리방식이 적용되므로 향상된 처리속도를 보장한다. 그리고 제안된 방법의 실효성을 보이기 위해 몇 가지 실험 결과를 제공한다.

A Jarque-Bera type test for multivariate normality based on second-power skewness and kurtosis

  • Kim, Namhyun
    • Communications for Statistical Applications and Methods
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    • 제28권5호
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    • pp.463-475
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    • 2021
  • Desgagné and de Micheaux (2018) proposed an alternative univariate normality test to the Jarque-Bera test. The proposed statistic is based on the sample second power skewness and kurtosis while the Jarque-Bera statistic uses sample Pearson's skewness and kurtosis that are the third and fourth standardized sample moments, respectively. In this paper, we generalize their statistic to a multivariate version based on orthogonalization or an empirical standardization of data. The proposed multivariate statistic follows chi-squared distribution approximately. A simulation study shows that the proposed statistic has good control of type I error even for a very small sample size when critical values from the approximate distribution are used. It has comparable power to the multivariate version of the Jarque-Bera test with exactly the same idea of the orthogonalization. It also shows much better power for some mixed normal alternatives.

Higher Order Moments of Record Values From the Inverse Weibull Lifetime Model and Edgeworth Approximate Inference

  • Sultan, K.S.
    • International Journal of Reliability and Applications
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    • 제8권1호
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    • pp.1-16
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    • 2007
  • In this paper, we derive exact explicit expressions for the triple and quadruple moments of the lower record values from inverse the Weibull (IW) distribution. Next, we present and calculate the coefficients of the best linear unbiased estimates of the location and scale parameters of IW distribution (BLUEs) for different choices of the shape parameter and records size. We then use the higher order moments and the calculated BLUEs to compute the mean, variance, and the coefficients of skewness and kurtosis of certain linear functions of lower record values. By using the coefficients of the skewness and kurtosis, we develop approximate confidence intervals for the location and scale parameters of the IW distribution using Edgeworth approximate values and then compare them with the corresponding intervals constructed through Monte Carlo simulations. Finally, we apply the findings of the paper to some simulated data.

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A bivariate extension of the Hosking and Wallis goodness-of-fit measure for regional distributions

  • Kjeldsen, Thomas Rodding;Prosdocimi, Ilaria
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2015년도 학술발표회
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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.

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