LAUSR

The parametric estimation and optimal censoring scheme are considered under the progressive multi-stage Type-I censoring scheme as well as step-stress accelerated lifetime model. Nonparametric estimators, using the information of the observable numbers of failures and numbers of censored units at the censoring times, are used to derive estimates of the reliability function at the censoring times. Then two parametric estimators, the maximum likelihood and the minimum-distance, are used to estimate the unknown Euclidean parameters of a parametric model. We use D-optimality criterion to determine an optimal sequential step-stress plan under progressive Type-I censoring. Simulation studies are also conducted to assess the finite performance of our estimators.