A MCMC-type simple probabilistic approach for determining optimal progressive censoring schemes

Abstract

We present here a simple probabilistic approach for determining an optimal progressive censoring scheme by defining a probability structure on the set of feasible solutions. Given an initial solution, the new updated solution is computed within the probabilistic structure. This approach will be especially useful when the cardinality of the set of feasible solutions is large. The validation of the proposed approach is demonstrated by comparing the optimal scheme so determined with the one obtained by exhaustive numerical search.

Keywords:

• Life-testing experiment
• Near-optimal solution
• Optimal progressive censoring
• Quantile
• Variance measure
• Cost criterion

Acknowledgments

The authors express their sincere thanks to two anonymous referees and an associate editor for their critical comments and valuable suggestions which have resulted in an improvement over the earlier version of the manuscript. The second author thanks the National Sciences and Engineering Research Council of Canada for supporting this research through an Individual Discovery Grant RGPIN-2020-06733.