Full posterior analysis of three parameter lognormal distribution using gibbs sampler

Abstract

The paper provides full posterior analysis of three parameter lognormal distribution using Gibbs Sampler, an important and useful Markov chain Monte Carlo technique in Bayesian computation. The extension of the algorithm is given to cover the case of censored data. It has been found that the censoring which creates special problem in the analysis of lognormal model with non-closed form cdf, can be routinely tackled by the use of Gibbs sampler. Suitable numerical illustrations are provided for both complete and censored situations.