Publications and Preprints

In accelerated life testing, the products are tested at high stress conditions and the results are used to draw inferences about the product lifetime at the normal stress condition. The products can fail due to one of the several possible causes of failure which need not be independent. In this paper, we consider the accelerated life testing in the presence of dependent competing risks. We propose suitable models using the subsurvival functions for the data arising from such situations and carry out the estimation of the parameters involved in the models. Finally, the method is applied to a real data.