Journal ArticleDOI
A Comparison of Maximum Likelihood and Bayesian Estimators for the Three-Parameter Weibull Distribution
Richard Smith,J. C. Naylor +1 more
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.read more
Citations
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Book ChapterDOI
Bayes Quantile Estimation and Threshold Selection for the Generalized Pareto Family
TL;DR: An interactive program for analyzing observations above a high threshold using parameter estimators which are not too efficient but easy to compute to find the empirical optimal combination choice of threshold and choice of monotone increasing function transformation.
The gamma-weibull distribution
TL;DR: An extension of the Weibull distribution which involves an additional shape parameter is proposed in this article, where the additional parameter acts somewhat as a location parameter while the support of the distribution remains the positive half-line.
Journal ArticleDOI
On the existence of the nonlinear weighted least squares estimate for a three-parameter Weibull distribution
TL;DR: The problem of nonlinear weighted least squares fitting of the three-parameter Weibull distribution to the given data (wi,ti,yi), i=1,...,n, is considered and it is shown that the best least squares estimate exists.
Journal ArticleDOI
Skew t distributions via the sinh-arcsinh transformation
TL;DR: In this article, a sinh-arcsinh transformation is used to generate a skew extension of Student's t distribution, which provides an alternative to previously proposed skew t distributions, and the basic properties of the resulting sinharcsinhed t family of distributions are presented, many of them effectively having the same level of complexity as their Student t counterparts.
References
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Journal ArticleDOI
Statistical Models and Methods for Lifetime Data.
Brian Francis,Jerald F. Lawless +1 more
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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