NONPARAMETRIC INFERENCES FOR RAMP STRESS TESTS UNDER RANDOM CENSORING

This paper considers nonparametric estimation of lifetime distribution of a product under ramp stress accelerated life tests in which the st ress on an item increases linearly with time and observations are rand omly censored. Assuming that a cumulative exposure model holds, the li fetime distribution of an item under ramp stress is derived. Three non parametric estimators of the lifetime distribution at use condition st ress are obtained for the situation where the time transformation func tion relating stress to lifetime distributions of a test item is a ver sion of the inverse power law. The proposed estimators are robust to u nderlying lifetime distribution and are computed in closed form. They are compared with maximum likelihood estimator for small samples under exponential lifetime distribution. The method is extended to the case of competing risks.