• 한국해안해양공학회지
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• 제19권4호
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• pp.313-319
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• 2007

장기간의 극치 및 평상시 파고는 연안 및 항만구조물의 계획 및 설계에서 매우 중요한 환경인자이다. 그러나, 한국 연안 심해파의 관측 자료가 한정되어 있기 때문에, 심해설계파의 정보는 기상정보로부터 사후추정 한 장기간의 파랑자료를 이용하고 있다. 본 연구에서는 한국해양연구원(2003)에서 제시한 1979년부터 1998년까지의 한국연안 67개 지점의 16방향별 최대 유의파 산출자료를 이용하여 극치분포 분석을 수행하였다. 특성분석에 사용된 극치분포함수는 FT-I과 Weibull 분포이며, 각 분포함수의 매개변수는 Goda(2004)의 방법을 이용하여 추정하였다. 또한 Goda and Gobune(1990)가 제안한 MIR 값을 산정하여 가장 적합한 확률분포형을 결정하였다. 분석결과 FT-I 분포가 886개 지점, Weibull(k=0.75) 분포가 81개 지점 및 Weibull(k=1.00) 분포가 105개 지점의 확률분포형으로 적합한 것으로 판단된다.

• Journal of the Korean Data and Information Science Society
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• 제7권1호
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• pp.37-46
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• 1996

계단충격가속수명시험에서 얻은 자료를 토대로 통계적 추론을 위해 가정하는 수명분포에 대한 적합도 검정을 Kolmogorov-Smirnov, Cramer-von Mises, Anderson-Darling과 같은 비모수적 검정통계량들을 이용한 검정절차를 제안하고, 각 통계량들을 검정력 측면에서 비교하고자 한다.

• 품질경영학회지
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• 제22권2호
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• pp.69-78
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• 1994

We obtain the Bayes estimator(BE), the minimum variance unbiased estimator(MVUE) and maximun likelihood estimator(MLE) of the reliability when the distribution of the stress and the strength are Weibull with known shape parameters. The experiment is terminated before all of the items on the test have failed and the failed items are partially replaced. Performance of the three estimators for moderate size samples are compared through Monte Carlo simulation.

• 한국신뢰성학회지:신뢰성응용연구
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• 제14권1호
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• pp.45-51
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• 2014

Thermal shock tests at two stress levels were performed to see the life (cycles) of LPF ASSY (low pass filter assembly) at normal stress level. In this case Coffin-Manson relationship is generally used to describe the relationship between the temperature difference and the life, together with the Weibull distribution describing the life at each stress level. So for given data Coffin-Manson is fitted to predict the life at normal stress level. However, different types of models are appropriate for this type of test. Hence, a more appropriate model such as General log-linear model which can also incorporate the duration at the highest and lowest temperatures and acceleration time will be introduced.

• 태양에너지
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• 제4권2호
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• pp.3-12
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• 1984

In this paper, how to design the wind power generation system is presented. It is shown that the wind system optimization can be achieved by consideration of the four factors; wind statistics, efficiency of conversion of wind energy to electrical energy, average annual energy extracted and load factor. The wind is characterized by a weibull probability function. The Weibull parameter is calculated for the characterizing wind and the primary design specification of ten different sites. Some graphs are presented, which can be used to design a wind system for maximum output of a specified load factor at given site. Two different systems, $V_c=0.4V_R$ and $V_c=0.5V_R$ are discussed, as samples, for investigation of the effects on the system through the variation of cut-in speed.

• Journal of the Korean Data and Information Science Society
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• 제16권4호
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• pp.1017-1026
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• 2005

We consider the problem of modeling count data where the observation period is determined by the survival time of the individual under study. We assume random effects or frailty model to allow for a possible association between the death times and the counts. We assume that, given a random effect, the death times follow a Weibull distribution with a rate that depends on some covariates. For the counts, given the random effect, a Poisson process is assumed with the intensity depending on time and the covariates. A gamma model is assumed for the random effect. Maximum likelihood estimators of the model parameters are obtained. The model is applied to data set of patients with breast cancer who received a bone marrow transplant. A model for the time to death and the number of supportive transfusions a patient received is constructed and consequences of the model are examined.

• Communications for Statistical Applications and Methods
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• 제13권1호
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• pp.191-204
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• 2006

This paper develops a Bayesian method to derive the optimal sequential preventive maintenance(PM) policy by determining the PM schedules which minimize the mean cost rate. Such PM schedules are derived based on a general sequential imperfect PM model proposed by Lin, Zuo and Yam(2000) and may have unequal length of PM intervals. To apply the Bayesian approach in this problem, we assume that the failure times follow a Weibull distribution and consider some appropriate prior distributions for the scale and shape parameters of the Weibull model. The solution is proved to be finite and unique under some mild conditions. Numerical examples for the proposed optimal sequential PM policy are presented for illustrative purposes.

• 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.

• 응용통계연구
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• 제11권2호
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• pp.351-362
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• 1998

공학의 응용분야인 신뢰수명론에서 와이블분포는 매우 중요한 역할을 해왔다. 그러나 와이블분포는 분포자체가 가지고 있는 형상모수의 영향으로 인하여 적합도 청정에 있어서 어려움의 대상이 되어 왔다. 이 논문은 쿨백-레이블러 정보 (Kullback-Leibler Information)을 이용한, 와이블 분포의 모수들에 영향을 받지 않은 검정 통계량을 제시함으로 위의 문제점을 해결하고, 제시된 검정 통계량에 대한 점근적 성질들과 결정력을 분석하였다. 제시된 검정 통계량은 기존의 결정 통계량들보다 검정력 비교에 있어서 더 우수한 검정력들을 보였고, 또한 실제 자료에 의한 적합도 검정의 예제를 보였다.

• 대한수학회논문집
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• 제34권4호
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• pp.1335-1352
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• 2019

In this article, a new family of lifetime distributions by adding two additional parameters is introduced. The new family is called, the logarithmic Kumaraswamy family of distributions. For the proposed family, explicit expressions for some mathematical properties are derived. Maximum likelihood estimates of the model parameters are also obtained. This method is applied to develop a new lifetime model, called the logarithmic Kumaraswamy Weibull distribution. The proposed model is very flexible and capable of modeling data with increasing, decreasing, unimodal or modified unimodal shaped hazard rates. To access the behavior of the model parameters, a simulation study has been carried out. Finally, the potentiality of the new method is proved via analyzing two real data sets.