• Communications for Statistical Applications and Methods
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• 제6권1호
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• pp.169-180
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• 1999

A Markov Chain Monte Carlo method with development of computation is used to be the software system reliability probability model. For Bayesian estimator considering computational problem and theoretical justification we studies relation Markov Chain with Gibbs sampling. Special case of GOS with Superposition for Goel-Okumoto and Weibull models using Gibbs sampling and Metropolis algorithm considered. In this paper discuss Bayesian computation and model selection using posterior predictive likelihood criterion. We consider in this paper data using method by Cox-Lewis. A numerical example with a simulated data set is given.

• 정보처리학회논문지D
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• 제15D권2호
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• pp.207-212
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• 2008

본 논문은 소프트웨어 비용추정 모델의 적합성을 평가하고, 가장 적합한 모델을 제시하였다. 먼저, 해당 모델의 함수를 변수변환시켜 선형식으로 만든다. 다음으로 실제 개발 소프트웨어의 비용 데이터가 모델의 선형식에 얼마나 적합한지로 모델의 성능을 평가한다. 모델 성능평가에는 절대오차 대신 상대오차 개념인 MMRE를 적용하였다. 기존의 소프트웨어 비용추정 모델은 Weibull, Gamma와 Rayleigh 함수를 따르고 있다. 본 논문에서는 성장곡선의 일종인 Gompertz 곡선 모델을 제안하였다. 추가로 다른 성장곡선들도 적합성을 검증하였다. 모델 성능평가 결과 Gompertz 성장곡선이 소프트웨어 비용추정 모델로 가장 적합한 성능을 보였다.

• Wind and Structures
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• 제31권4호
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• pp.311-319
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• 2020

India is a developing nation and heavily spends on the development of wind power plants to meet the national energy demand. The objective of this paper is to investigate wind power potential of Ennore site using wind data collected over a period of two years by three parameter Weibull distribution. The Weibull parameters are estimated using maximum likelihood, least square method and moment method and the accuracy is determined using R² and root mean square error values. The site specific capacity factor is calculated by the mathematical model developed by three parameter Weibull distribution at different hub heights above the ground level. At last, the wind energy economic analysis is carried out using capacity factor at 30 m, 40 m and 50 m height for different wind turbine models. The analysis showed that the site has potential to install utility wind turbines to generate energy at the lowest cost per kilowatt-hour at height of 50 m. This research provides information of wind characteristics of potential sites and helps in selecting suitable wind turbine.

• Industrial Engineering and Management Systems
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• 제6권1호
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• pp.1-10
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• 2007

The objective of this study is to develop an optimal joint cost from the perspectives of both the manufacturer and the retailer. The integrated production-inventory model with Weibull distribution deteriorating items is assumed to have a constant demand rate. A limited retailer storage space and multiple delivery per order are considered in this model. A numerical example including the sensitivity analysis is given to validate the results of the production-inventory model.

• 한국안전학회지
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• 제33권3호
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• pp.83-91
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• 2018

This paper suggests a weibull time delay model to evaluate failure risks in FMEA(failure modes and effects analysis). Assuming three types of loss functions for delayed time in failure cause detection, the risk of each failure cause is evaluated as its occurring frequency and expected loss. Since the closed form solution of the risk metric cannot be obtained, a statistical computer software R program is used for numerical calculation. When the occurrence and detection times have a common shape parameter, though, some simple results of mathematical derivation are also available. As an enormous quantity of field data becomes available under recent progress of data acquisition system, the proposed risk metric will provide a more practical and reasonable tool for evaluating the risks of failure causes in FMEA.

• Journal of the Korean Data and Information Science Society
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• 제7권2호
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• pp.263-272
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• 1996

임의의 기계에 대한 수명의 분포는 와이블분포를 하는 경우가 흔하다. 그리고 현실적으로 기계의 수명시간을 검정할 때, 시험시간및 여러 환경적인 제약에 의하여 표본으로 주어진 기계의 수명을 모두 관측하기는 어렵다. 그래서, 본 연구에서는 임의 중단모형 하에서 와이블분포의 모수를 최소제곱법(least squares method)을 이용하여 추정하고 기존의 최대우도추정량(maximum likelihood estimates)과 효율성의 측면에서 비교하고자 한다.

• Communications for Statistical Applications and Methods
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• 제31권1호
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• pp.55-64
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• 2024

In this study, we consider the sample size determination problem for clustered count data with many zeros. In general, zero-inflated Poisson and binomial models are commonly used for zero-inflated data; however, in real data the assumptions that should be satisfied when using each model might be violated. We calculate the required sample size based on a discrete Weibull regression model that can handle both underdispersed and overdispersed data types. We use the Monte Carlo simulation to compute the required sample size. With our proposed method, a unified model with a low failure risk can be used to cope with the dispersed data type and handle data with many zeros, which appear in groups or clusters sharing a common variation source. A simulation study shows that our proposed method provides accurate results, revealing that the sample size is affected by the distribution skewness, covariance structure of covariates, and amount of zeros. We apply our method to the pancreas disorder length of the stay data collected from Western Australia.

• 한국신뢰성학회지:신뢰성응용연구
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• 제12권3호
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• pp.139-152
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• 2012

Successive and simultaneous sudden death tests are compared with the complete and Type II censored samples in terms of expected test duration and Total Time on Test(TTT) subject to the same number of failures in order to maintain the equal statistical precision under Weibull lifetime distribution with known shape parameter. Also, two sudden death tests under a proposed cost model are discussed and a numerical example is provided to illustrate the use of the proposed cost model.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.405-412
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• 2003

In this paper, we consider two components system which the lifetimes have a bivariate weibull distribution with random censored data. Here the censoring time is independent of the lifetimes of the components. We construct large sample tests for independence and symmetry between two-components based on maximum likelihood estimators and the natural estimators. Also we present a numerical study.

• 품질경영학회지
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• 제28권3호
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• pp.1-10
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• 2000

In this paper, we address the Bayesian hypotheses testing for the comparison of Weibull distributions. In Bayesian testing problem, conventional Bayes factors can not typically accommodate the use of noninformative priors which are Improper and are defined only up to arbitrary constants. To overcome such problem, we use the recently proposed hypotheses testing criterion called the intrinsic Bayes factor. We derive the arithmetic and median intrinsic Bayes factors for the comparison of Weibull lifetime model and we use these results to analyze real data sets.