• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.268-275
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• 2003

We consider the Bayesian accelerated failure time model. The error distribution is assigned a skewed normal distribution which is including normal distribution. For noninformative priors of regression coefficients, we show the propriety of posterior distribution. A Markov Chain Monte Carlo algorithm(i.e., Gibbs Sampler) is used to obtain a predictive distribution for a future observation and Bayes estimates of regression coefficients.

• 응용통계연구
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• 제27권5호
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• pp.809-818
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• 2014

다변량 왜정규분포는 다변량 정규분포를 포함하는 분포로 최근 많은 응용분야에서 활용되고 있다. 본 논문에서는 다변량 왜정규분포를 기반으로 하는 선형결합통계량의 분포함수에 대한 안장점근사를 다루었다. 이는 단변량 왜정규분포 기반 표본평균에 대한 Na와 Yu (2013)의 결과를 선형결합 및 다변량의 경우로 확장한 것이다. 모의실험과 실제자료분석을 통해 제안된 근사법의 유용성과 정확도를 확인하였다.

• Communications for Statistical Applications and Methods
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• 제19권3호
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• pp.345-358
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• 2012

표본선택 모형을 최우추정법으로 추정할 때 오차항의 분포를 제대로 가정하는 것이 매우 중요하다. 표본선택 모형의 선택 방정식과 본 방정식의 오차항 분포를 일반적으로 이변량 정규분포로 가정하지만, 이 가정이 오차항의 실제 분포를 과도하게 제약할 가능성이 있다. 본 연구는 표본선택 모형의 오차항 분포로 $S_U$-정규분포를 도입한다. $S_U$-정규분포는 분포의 비대칭성과 초과첨도를 허용한다는 측면에서 정규분포보다 훨씬 유연하면서, 동시에 정규분포를 극한분포의 형태로 포함하고 있다. 또한 정규분포처럼 다변량 분포함수가 존재하기 때문에 표본선택 모형과 같은 다변량 모형에서도 활용할 수 있다. 본 논문은 $S_U$-정규분포를 이용한 표본선택 모형에서 로그우도 함수와 조건부 기댓값을 도출하고, 시뮬레이션을 통해 정규분포 모형과 추정성과를 비교한다. 또한 자동차 보유 가구들의 자동차 유지비에 관한 실제 데이터를 이용하여 $S_U$-정규분포 표본선택 모형의 추정결과를 제시한다.

• Steel and Composite Structures
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• 제44권5호
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• pp.619-632
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• 2022

There are numerous structural details (Longitudinal beam, web plate, U-ribs and I-ribs) in the top and bottom plates of steel box girders, which have significant influences on the longitudinal stress (normal stress) distribution. Clarifying the influence of these structural details on the normal stress distribution is important. In this paper, the ultra-wide steel box girder with large cantilevers of the Jinhai Bridge in China, which is the widest cable-stayed bridge in the world, has been analyzed. A 1:4.5 scale laboratory model of the steel box girder has been manufactured, and the influence of structural details on the normal stress distribution in the top and bottom plates for four different load cases has been analyzed in detail. Furthermore, a three-dimensional finite element model has been established to further investigate the influence regularity of structural details on the normal stress. The experimental and finite element analysis (FEA) results have shown that different structural details of the top and bottom plates have varying effects on the normal stress distribution. Notably, the U-ribs and I-ribs of the top and bottom plates introduce periodicity to the normal stress distribution. The period of the influence of U-ribs on the normal stress distribution is the sum of the single U-rib width and the U-rib spacing, and that of the influence of I-ribs on the normal stress distribution is equal to the spacing of the I-ribs. Furthermore, the same structural details but located at different positions, will have a different effect on the normal stress distribution.

• 산업경영시스템학회지
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• 제29권2호
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• pp.97-103
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• 2006

Recently, the control chart is developed for monitoring processes with normal short production runs by the coefficient of variation(CV) characteristic for a normal distribution. This control chart does not work well in non-normal short production runs. And most of industrial processes are known to follow the non-normal distribution. Therefore, the control chart is required to be developed for monitoring the processes with non-normal short production runs by the CV characteristics for a non-normal distribution. In this paper, we suggest the control chart for monitoring the processes with a gamma short runs by the CV characteristics for a gamma distribution. This control chart is denoted by the gamma CV control chart. Futhermore evaluated the performance of the gamma CV control chart by average run length(ARL).

• Communications for Statistical Applications and Methods
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• 제15권3호
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• pp.325-332
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• 2008

We consider estimation of reliability P(Y < X) and distribution of the ratio when X and Y are independent uniform random variable and power function random variable, respectively and also consider the estimation problem when X and Y are independent uniform random variable and a half-normal random variable, respectively.

• 품질경영학회지
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• 제44권1호
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• pp.167-180
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• 2016

Purpose: The problem for the traditional control chart is that it is unable to monitor the very small fraction of nonconforming and the underlying distribution is the normal distribution. $Z_p$ control chart is useful where it controls the vert small fraction on nonconforming. In this study, we will design the $Z_p$ control chart in order to use under non-normal process. Methods: $Z_p$ is calculated not by failure rate based on attribute data but using variable data. Control limit for non-normal $Z_p$ control chart is designed based on ${\alpha}$-risk calculated by cumulative distribution function of Burr distribution. ${\beta}$-risk, which is for performance evaluation, obtains in the Burr distribution's cumulative distribution function and control limit. Results: The control limit for non-normal $Z_p$ control chart is designed based on Burr distribution. The sensitivity can be checked through ARL table and OC curve. Conclusion: Non-normal $Z_p$ control chart is able to control not only the very small fraction of nonconforming, but it is also useful when $Z_p$ distribution is non-normal distribution.

• 응용통계연구
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• 제29권4호
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• pp.571-579
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• 2016

이차형식 통계량의 분포함수에 대한 연구는 주로 다변량 정규분포의 가정하에서 진행되어 왔다. 최근 다변량 정규분포를 포함하는 다변량 왜정규분포에 대한 연구가 활발하다. 본 논문에서는 다변량 왜정규분포의 가정하에서 이차형식 통계량의 분포함수에 대한 근사를 다루었다. 근사의 방법으로는 소표본에서도 정확도가 뛰어난 근사법으로 알려진 안장점근사를 사용하였으며, 모의실험을 통해 그 정도를 확인하였다.

• 한국세라믹학회지
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• 제34권9호
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• pp.927-934
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• 1997

Static and cyclic fatigue tests were carried out for alumina specimen to study the statistical analyses (normal, lognormal and Weibull distribution) of fatigue lifetime data and nominal initial crack length data. Fatigue lifetime data followed Weibull distribution better than normal or lognormal distribution, for the shape parameter of the notched specimen was larger than that of the unnotched specimen. The nominal initial crack length data obtained from fatigue lifetime followed the lognormal and Weibull distribution better than normal distribution, for the coefficient of variation of the unnotched specimen was larger than that of the notched specimen, and shape parameter of unnotched specimen was smaller than that of the notched specimen.

• Journal of applied mathematics & informatics
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• 제27권5_6호
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• pp.1429-1433
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• 2009

The likelihood distance for the joint distribution of two multivariate normal distributions with common covariance matrix is explicitly derived. It is useful for identifying outliers which do not follow the joint multivariate normal distribution with common covariance matrix. The likelihood distance derived here is a good ground for the use of a generalized Wilks statistic in influence analysis of two multivariate normal data.