On the Completeness of Minimal Sufficient Statistics with Censored Observations

Abstract

The property of completeness, for the minimal sufficient statistics, is investigated in the context of life testing when the set of observations is censored at a fixed time or at a fixed order statistic. Nonparametric families are shown to retain completeness for the observed order statistics and some implications regarding unbiased estimators and similar tests are presented. Most of the common parametric models fail to possess completeness of minimal sufficient statistics under censored sampling in the one-sample, two-sample and regression situations.