The exponential distribution possesses an essential position in lifetime distribution study. In this paper, an endeavor has been made to fit the Bayesian inference procedures for exponential distribution, exponentiated exponential and the two-parameter extension of exponential distribution. keeping in mind the end goal to actualize Bayesian techniques to examine and applied to a real survival censored data, visualization of lung cancer survival data and demonstrate through utilizing Stan. Stan is a high level language written in a C++ library for Bayesian modeling. This model applies to survival censoring data with the goal that every one of the ideas and calculations will be around similar data. Stan code has been created and enhanced to actualize a censored system all through utilizing Stan technique. Moreover, parallel simulation tools are also implemented and additionally actualized with a broad utilization of rstan.
