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International Journal of Statistika and Mathematika, ISSN: 2277- 2790 E-ISSN: 2249-8605

Volume 7, Issue 2, September 2013 pp 37-48

Research Article

Bayesian Estimation and Prediction of Exponentiated Weibull Model


Shankar Kumar Shrestha1, Vijay Kumar2

1Public Youth Campus, Tribhuvan University, Kathmandu, NEPAL.

2Department of Mathematics and Statistics, DDU Gorakhpur University, Gorakhpur-273009, Uttar Pradesh, INDIA.

Academic Editor:  Dr. Dase R.K.


This paper deals with the Bayesian estimation and prediction of three-parameter exponentiated Weibull distribution. The parameters are estimated using likelihood based inferential procedure: classical as well as Bayesian.The quasi Newton-Raphson algorithm is applied to obtain the maximum likelihood estimates and associated probability intervals. The Bayesian estimates of the parameters of exponentiated Weibull distribution are obtained using Markov chain Monte Carlo (MCMC) simulation method. We have obtained the probability intervals for parameters, hazard and reliability functions. The posterior predictive check procedure is used for evaluating model fit. All the Bayesian computations are performed in OpenBUGS and R software.  A real data set is analyzed for illustration of the proposed Bayesian approach.

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