Different Estimation Methods for Constant Stress Accelerated Life Test under Exponentiated Pareto Distribution

Accelerated life testing is used to measure the lifetime of highly reliable products. These products can work for a long time under normal use conditions, however, the producers want to know their lifetime before marketing. To accelerate the lifetime of a product, the high stress is applied. In this study, we assumed that the lifetime of a product at constant stress level follows exponentiated Pareto distribution. To estimate the parameters of the model, the maximum likelihood, the least squares, the weighted least squares, the maximum product of spacing, minimum spacing absolute-log distance and the minimum distance methods, namely, the Cramér-von Mises, the Anderson-Darling and right-tail Anderson-Darling methods are used. The performances of the proposed estimates are compared via the Monte-Carlo simulation study. A real data set is analysed for illustrative purposes.