Asymptotic Theory of Triple Sampling for Sequential Estimation of a Mean

Abstract

We describe the asymptotic theory of triple sampling as it pertains to the estimation of a mean. We obtain limit theorems for the case of the normal distribution. Our results show that triple sampling combines the simplicity of Stein's double sampling technique with the efficiency of the fully sequential Anscombe-Chow-Robbins procedure.