Robustly Estimating Lower Percentiles When Observations Are Costly

This article illustrates the effective use of Bayesian methods for the estimation of lower percentiles for the breaking strengths of materials. The method is presented in conjunction with the technique of median censoring, which censors reliability data at a point just slightly larger than the median. As a result, median censoring allows users to safeguard against different failure mechanisms with greater weight placed on the smaller observations when model fitting. Additionally, Bayesian techniques may enable one to use less data from the production line for destructive testing.