Bootstrapping-based fixed-width confidence intervals for ranking and selection

Abstract

A ranking and selection (R&S) procedure allowing comparisons between systems to be made based on any distributional property of interest would be useful. This paper presents initial work toward the development of such a procedure. Previously published work gives a method for using bootstrapping to develop fixed-width confidence intervals with a specified coverage probability around a property of interest. Empirical evidence is provided in support of the use of this approach for building fixed-width confidence intervals around both means and quantiles. Additionally, the use of fixed-width confidence intervals for bootstrapped R&S is demonstrated. For two systems, R&S is performed by building a confidence interval around the difference between two systems. Simultaneous fixed-width confidence intervals are used for R&S on more than 2 systems, and the approach is demonstrated for three systems. The technique is shown to be effective for R&S based on both quantiles and means.