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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2771

Title: Comparison of estimates using record statistics from Weibull model: Bayesian and non-Bayesian approaches
Authors: Soliman, Ahmed A.
Abd Ellah, A.H.
Sultan, K.S.
Keywords: Record values
Symmetric and asymmetric loss functions
Maximum likelihood estimates
Bayesian estimation and prediction
Monte
Carlo simulation
Issue Date: 2006
Publisher: Elesiever
Citation: Computational Statistics & Data Analysis: 51; 2065 – 2077
Abstract: This paper develops a Bayesian analysis in the context of record statistics values from the two-parameter Weibull distribution. The ML and the Bayes estimates based on record values are derived for the two unknown parameters and some survival time parameters e.g. reliability and hazard functions. The Bayes estimates are obtained based on a conjugate prior for the scale parameter and a discrete prior for the shape parameter of this model. This is done with respect to both symmetric loss function (squared error loss), and asymmetric loss function (linear-exponential (LINEX)) loss function. The maximum likelihood and the different Bayes estimates are compared via a Monte Carlo simulation study. A practical example consisting of real record values using the data from an accelerated test on insulating fluid reported by Nelson was used for illustration and comparison. Finally, Bayesian predictive density function, which is necessary to obtain bounds for predictive interval of future record is derived and discussed using a numerical example. The results may be of interest in a situation where only record values are stored.
Description: Author: Abd Ellah, A.H. - Department of Mathematics, Teachers College, P.O. Box 4341, Riyadh 11491, Saudi Arabia Author: Sultan, K.S. - Department of Statistics & Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
URI: www.elsevier.com/locate/csda
http://hdl.handle.net/123456789/2771
ISSN: 2065–2077
10.1016/j.csda.2005.12.020
Appears in Collections:College of Science

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