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

Volume 9, Issue 2, March 2014 pp 66-81

Research Article

Bayesian Estimation of Three-Parameter Exponentiated Log-logistic Distribution

Arun Kumar Chaudhary¹, Vijay Kumar²

¹Nepal Commerce Campus, Tribhuvan University, Kathmandu, NEPAL.

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

Academic Editor: Dr. Dase R. K.

                In this paper, we have considered the estimation problem of three-parameter exponentiated log-logistic distribution. The parameters are estimated using likelihood based inferential procedure: classical as well as Bayesian. We have computed MLEs and Bayes estimates under informative and non-informative priors along with their asymptotic confidence, bootstrap and HPD intervals. The Bayesian estimates of the parameters of exponentiated log-logistic 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 has been applied for evaluating the model fit. All the computations are performed in OpenBUGS and R software.  A real data set is analyzed for illustration of the proposed inferential procedures.