2-STAGE STOPPING PROCEDURES BASED ON STANDARDIZED TIME-SERIES

We propose some new two-stage stopping procedures to construct absolut e-width and relative-width confidence intervals for a simulation estim ator of the steady-state mean of a stochastic process. The procedures are based on the method of standardized time series proposed by Schrub en and on Stein's two-stage sampling scheme. We prove that our two-sta ge procedures give rise to asymptotically valid confidence intervals ( as the prescribed length of the confidence interval approaches zero an d the size of the first stage grows to infinity). The sole assumption required is that the stochastic process satisfy a functional central l imit theorem.