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.