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Journal ArticleDOI

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

Richard Smith, +1 more
- 01 Nov 1987 - 
- Vol. 36, Iss: 3, pp 358-369
TLDR
In this article, maximum likelihood and Bayesian estimators are developed and compared for the three-parameter Weibull distribution, and the authors conclude that there are practical advantages to the Bayesian approach.
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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Citations
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Maximum Likelihood Estimation in the 3-parameter Weibull Distribution A Look through the Generalized Extreme-value

TL;DR: In this article, a Monte Carlo simulation using the newly developed generalized extreme-value distribution parameter estimation code reveals the property of the percentile point estimates for extreme value type distributions, when the Weibull shape parameter is large.
Journal ArticleDOI

Weighted Quasi Akash Distribution:: Properties and Applications

TL;DR: In this paper, a three-parameter weighted quasi Akash distribution (WQAD) is proposed, which includes twoparameter weighted Akash, quasi-Akash and gamma distributions as special cases.
Journal ArticleDOI

An alternative to the weibull distribution

TL;DR: In this paper, a "selection probability function" is proposed which represents the probability that a unit of given strength survives to be tested, and when combined with an underlying Weibull strength distribution, yields a distribution simi
Journal ArticleDOI

Zero-Truncated Poisson Exponentiated Gamma Distribution: Application and Estimation Methods

TL;DR: The zero-truncated Poisson exponentiated gamma distribution (ZPGD) as mentioned in this paper is a two-parameter lifetime model with only two parameters, which allows to fit more dispersed data.
Journal ArticleDOI

Bayesian and maximum likelihood estimations from parameters of McDonald Extended Weibull model based on progressive type-II censoring

TL;DR: In this paper, the authors considered the statistical inference of the six-parameter McDonald extended Weibull distribution (McEW) based on the progressively Type-II censored sample.
References
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Book

Statistics of extremes

E. J. Gumbel
Journal ArticleDOI

Statistics of Extremes.

B. F. Kimball, +1 more
- 01 Mar 1961 - 
Journal ArticleDOI

Maximum likelihood estimation in a class of nonregular cases

TL;DR: In this article, the authors consider maximum likelihood estimation of the parameters of a probability density which is zero for x 2, the information matrix is finite and the classical asymptotic properties continue to hold.
Journal ArticleDOI

Estimating Parameters in Continuous Univariate Distributions with a Shifted Origin

TL;DR: In this paper, a general method of estimating parameters in continuous univariate distributions is proposed, which is especially suited to cases where one of the parameters is an unknown shifted origin and is shown to give consistent estimators with asymptotic efficiency equal to ML estimators when these exist.
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