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A Comparison of Maximum Likelihood and Bayesian Estimators for the Three- Parameter Weibull Distribution

1987/01/01 by Richard L. Smith, J. C. Naylor · 1 citation
Decision Sciences · Mathematics · #Probabilistic and Robust Engineering Design #Statistical Distribution Estimation and Applications #Statistical Methods and Inference

paper · doi:10.2307/2347795

crossref issued 1987/01/01 · crossref published 1987/01/01 · crossref published-print 1987/01/01 · openalex publication_date 1987/01/01 · crossref created 2006/06/18 · crossref deposited 2021/07/20 · openalex created_date 2025/10/10 · crossref indexed 2026/07/29 · openalex updated_date 2026/07/30

Abstract

Maximum likelihood and Bayesian estimators are developed and compared for the three‐parameter Weibull distribution. For the data analysed in the paper, the two sets of estimators are found to be very different. The reasons for this are explored, and ways of reducing the discrepancy, including reparametrization, are investigated. Our overall conclusion is that there are practical advantages to the Bayesian approach.

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