Nonparametric Estimation and Goodness of Fit Testing of Hypotheses for Distributions in Accelerated Life Testing

摘要

In this paper we present a nonparametric approach to accelerated life testing by deleting the requirement that the common parametric family of life distributions under all the stresses be specified in advance. We do retain the requirement that the time transformation function be specified, and consider a version of the familiar inverse power law. We show how the data from the accelerated life test can be used to obtain a consistent estimate of the failure distribution at use conditions stress, and test the hypotheses that the underlying failure distributions belong to a specified family of distributions. We also show how to obtain approximate uniform confidence bounds for the failure distribution at use conditions stress. We illustrate our approach by considering some real life data. (Author)