Bayesian Estimation of Reliability of the ElectronicComponents Using Censored Data from WeibullDistribution: Different Prior Distributions

The Weibull distribution has been widely used in survival and engineering reliability analysis. In life testing experiments is fairlycommon practice to terminate the experiment before all the items havefailed, that means the data are censored. Thus, the main objective ofthis paper is to estimate the reliability function of the Weibulldistribution with uncensored and censored data by using Bayesianestimation. Usually it is assigned prior distributions for theparameters (shape and scale) of the Weibull distribution. Instead, weassign prior distributions for the reliability function for a fixed time,that is, for the parameter of interest. For this, we propose differentnon-informative prior distributions for the reliability function andselect the one that provides more accurate estimates. Some examplesare introduced to illustrate the methodology and mainly to investigatethe performance of the prior distributions proposed in the paper. TheBayesian analysis is conducted based on Markov Chain Monte Carlo(MCMC) methods to generate samples from the posteriordistributions