ON THE BAYESIAN ANALYSIS OF EXTENDED WEIBULL-GEOMETRIC DISTRIBUTION
DOI:
https://doi.org/10.13052/jrss2229-5666.12210Keywords:
Extended Weibull Distribution, Mcmc, Bayes Estimator, Posterior Risk, Loss Function, Precautionary Loss FunctionAbstract
The paper deals with the Bayes estimation of Extended Weibull-Geometric (EWG) distribution. In particular, we discuss Bayes estimators and their posterior risks using the noninformative and informative priors under different loss functions. Since the posterior summaries cannot be obtained analytically, we adopt Markov Chain Monte Carlo (MCMC) technique to assess the performance of Bayes estimates for different sample sizes. A real life example is also part of this study.
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