Bayesian Analysis of the Weibull lifetimes under type-I Ordinary Right Censored Samples

Abstract

Censoring is an unavoidable feature of reliability and survival analysis due to time and cost constraints. In this paper, we numerically study the effect of sample size, censoring rate and parameter size of Weibull distribution on its estimates. Some interesting properties and comparison of the Bayes and ML estimates along with their standard errors have been studied. The sample expressions for the Bayes and ML estimates and their variances are derived as a function of test termination time. The difference between ML estimates and uninformative Bayesian estimates becomes negligible for large sample size.