Book Description
Step-stress models form an essential part of accelerated life testing procedures. Under a step-stress model, the test units are exposed to stress levels that increase at intermediate time points of the experiment. The goal is to develop statistical inference for, e.g., the mean lifetime under each stress level, targeting to the extrapolation under normal operating conditions. This is achieved through an appropriate link function that connects the stress level to the associated mean lifetime. The assumptions made about the time points of stress level change, the termination point of the experiment, the underlying lifetime distributions, the type of censoring (if present), and the way of monitoring lead to alternative models. Step-stress models can be designed for single or multiple samples. We discuss recent developments in designing and analyzing step-stress models based on hazard rates. The inference approach adopted is mainly the maximum likelihood, but Bayesian approaches are briefly discussed.
