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http://dx.doi.org/10.7232/JKIIE.2016.42.4.256

A Comparison of the Reliability Estimation Accuracy between Bayesian Methods and Classical Methods Based on Weibull Distribution  

Cho, HyungJun (Department of Industrial and Management Engineering, Kyonggi University Graduate School)
Lim, JunHyoung (Department of Industrial and Management Engineering, Kyonggi University)
Kim, YongSoo (Department of Industrial and Management Engineering, Kyonggi University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.42, no.4, 2016 , pp. 256-262 More about this Journal
Abstract
The Weibull is widely used in reliability analysis, and several studies have attempted to improve estimation of the distribution's parameters. least squares estimation (LSE) or Maximum likelihood estimation (MLE) are often used to estimate distribution parameters. However, it has been proven that Bayesian methods are more suitable for small sample sizes than LSE and MLE. In this work, the Weibull parameter estimation accuracy of LSE, MLE, and Bayesian method are compared for sample sets with 3 to 30 data points. The Bayesian method was most accurate for sample sizes under 25, and the accuracy of the Bayesian method was similar to LSE and MLE as the sample size increased.
Keywords
Weibull Distribution; Sample Sizes; Least Square Estimation; Maximum Likelihood Estimation; Bayesian Method;
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Times Cited By KSCI : 3  (Citation Analysis)
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