Comparison of some bayes' estimators for the weibull reliability function under different loss functions

Abstract EN

Weibull distribution is one of the most widely used distributions of lifetime in reliability engineering.

It has the ability to provide reasonably accurate failure analysis and failure forecasts especially with extremely small samples.

Bayesian approach has received a lot of attention along with the traditional methods of estimation such as maximum likelihood and moment estimation methods.

The object of the present paper is to compare some Bayes' estimators for the scale Parameter of the Weibull reliability function using different loss functions, based on Jeffrey prior information for estimating the scale parameter of Weibull distribution.

The comparison was based on a Monte Carlo study.

Through the simulation study comparison was made on the performance of these estimators with respect to the mean square error (MSE) and the mean percentage error (MPE).

The results of comparison by MSE showed that the Weibull reliability function based upon squared error loss function was the best followed by the modified El- Sayyad's loss function.

While comparison by MPE showed the reverse.