Accelerated sequential procedure for selecting the largest mean
Nitis Mukhopadhyay, Tumulesh K. S. Solanky, Nitis Mukhopadhyay · Sequential Analysis · 1992
From K(≧2) independent normal populations, we wish to select the one associted with the largest mean, assuming that the comman variance is unknown. We adopt the “indifference Zone” approach of Bechhofer (1954) and propose an accelerated version of the purely sequential procedure of Robbins et al. (1968). Asymptotic second order expansions for the probability of correct selection and other characteristices of this modified rule are provided for arbitrary K. We discuss both small and moderate sample size performances of our stopping time via computer simlations and note that the accelearted version can save considearable amout of sampling operations, yet it can be very competitive with the classical sampling procedure of Robbins et al. (1968).