Nonparametric Age Replacement: Bootstrap Confidence Intervals for the Optimal Cost

Bootstrap confidence intervals for the actual cost of using a given nonparametric estimate of the optimal age replacement strategy are shown to have the claimed coverage probability. A numerical algorithm is given to obtain these confidence intervals in practice. The small sample behavior of these confidence intervals is illustrated by simulations. Finally, comparisons are made with the confidence interval obtained from asymptotic normal theory. We show that the bootstrap confidence interval is the one to use in age replacement problems.