Bayesian estimation of two-parameter Weibull distribution using extension of Jeffreys prior information with three loss functions
type: Item
instance of: scholarly article
title: Bayesian estimation of two-parameter Weibull distribution using extension of Jeffreys prior information with three loss functions
zbMATH Open document ID: 1264.62023
DOI: 10.1155/2012/589640
author: Chris Bambey Guure
author: Noor Akma Ibrahim
author: Al Omari Mohammed Ahmed
published in: Mathematical Problems in Engineering
publication date: 2013-06-11T00:00:00Z
review text: Summary: The Weibull distribution has been observed as one of the most useful distribution for modelling and analysing life time data in engineering, biology, and others. Studies have been done vigorously in the literature to determine the best method for estimating its parameters. Recently, much attention has been given to the Bayesian estimation approach for parameter estimation which is in contention with other estimation methods. We examine the performance of the maximum likelihood estimator and Bayesian estimator using extensions of the Jeffreys prior information with three loss functions, namely, the linear exponential loss, general entropy loss, and the square error loss function for estimating the two-parameter Weibull failure time distribution. These methods are compared using the mean squared error through simulation studies with varying sample sizes. The results show that the Bayesian estimator using extensions of Jeffreys' prior under linear exponential loss functions in most cases gives the smallest mean squared error and the absolute bias for both the scale parameter \(\alpha\) and the shape parameter \(\beta\) for the given values of the extension of Jeffreys' prior.
Mathematics Subject Classification ID: 62F15
Mathematics Subject Classification ID: 62F10
zbMATH DE Number: 6173405
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/589640
OpenAlex ID: W2115653605
Wikidata QID: Q58912216
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description: scientific article; zbMATH DE number 6173405