Abstract
In manufacturing industries and several other fields, accelerated life testing is used widely to obtain sufficient failure time data of test units quickly as compared to normal use conditions. It is assumed that the lifetime of a product at constant stress level follows generalized inverse Lindley distribution. It is a common observation that while estimating the parameters of a model, one usually adopts the maximum likelihood estimation method as the starting point. In this paper, we consider eight frequentist methods of estimation, besides using the maximum likelihood method for estimating the parameters of the generalized inverse Lindley distribution under constant stress accelerated life test. In addition, the shape parameter and the reliability function of the model under usual conditions are obtained using nine considered estimation methods. Monte Carlo simulations are performed for investigating the performances of the considered methods in terms of their mean relative estimates and mean square errors using small, medium and large sample sizes. One accelerated life test data set is analyzed for illustrative purposes. In addition, bootstrap confidence intervals of the parameters are obtained as part of data analysis based on the considered estimation methods.