Journal of Korean Institute of Industrial Engineers (대한산업공학회지)

Korean Institute of Industrial Engineers (대한산업공학회)
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A Comparison of the Reliability Estimation Accuracy between Bayesian Methods and Classical Methods Based on Weibull Distribution

와이블분포 하에서 베이지안 기법과 전통적 기법 간의 신뢰도 추정 정확도 비교

  • 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)
  • 조형준 (경기대학교 일반대학원 산업경영공학과) ;
  • 임준형 (경기대학교 산업경영공학과) ;
  • 김용수 (경기대학교 산업경영공학과)
  • Received : 2016.02.05
  • Accepted : 2016.05.25
  • Published : 2016.08.15
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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.

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References

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