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

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

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 repara...

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Veröffentlicht in:Applied Statistics 1987-01, Vol.36 (3), p.358-369
Hauptverfasser: Smith, Richard L., Naylor, J. C.
Format: Artikel
Sprache:eng
Schlagworte:
Analytical estimating
Applied sciences
Bayesian inference
Data sampling
Estimators
Exact sciences and technology
Generalised Extreme Value distribution
Goodness of fit
Inference
Maximum likelihood
Maximum likelihood estimation
Maximum likelihood estimators
Nose distribution
Operational research and scientific management
Operational research. Management science
Reliability theory. Replacement problems
Sampling distributions
Standard deviation
Standard error
Three‐parameter Weibull distribution
Weakest link model
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Zusammenfassung: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.
ISSN:0035-9254
1467-9876
DOI:10.2307/2347795