Inferences on a simple step-stress model with type-II censored exponential data

This paper presents the inferences of parameters on the simple step-stress model in accelerated life testing with type-II censoring. An exponential life distribution with a mean that is a log-linear function of stress, and a cumulative exposure model are assumed. Maximum likelihood methods are used to estimate the parameters of these models. Hypothesis tests about model parameters are discussed. Confidence intervals for parameter-estimates are constructed using a pivotal quantity. The advantage of these results is that they apply to any sample size. A numerical example illustrates the inferential procedure.