Open AccessBayesian Analysis of Two-Parameter Exponentiated Log-logistic Distribution
Author(s) -
Arun Kumar Chaudhary
Publication year - 2020
Publication title -
pravaha
Language(s) - English
Resource type - Journals
ISSN - 2350-854X
DOI - 10.3126/pravaha.v25i1.31864
Subject(s) - markov chain monte carlo , mathematics , prior probability , statistics , bayesian probability , bayes' theorem , metropolis–hastings algorithm , markov chain , computer science
In this paper, the parameters of the two-parameter exponentiated log-logistic distribution based on a complete sample are estimated using the Markov chain Monte Carlo (MCMC) method. In order to perform full Bayesian analysis of the two-parameter exponentiated log-logistic distribution, the procedures are developed using the MCMC simulation method in Open BUGS, established software. The researcher has obtained the Bayes estimates of the parameters and their probability intervals are presented. The researcher has also discussed the estimation of the reliability function. For illustration under independent gamma priors, the real data set is considered.