On the Performance Characteristics of a Closed Adaptive Sequential Procedure for Selecting the Best Bernoulli Population.

摘要

In a recent paper, Bechhofer and Kulkarni proposed closed adaptive sequential procedures for a general class of k-population Bernoulli selection goals. These sequential selection procedures achieve the same probability of a correct selection, uniformly in the unknown single-trial 'success' probabilities pi (1 < or = i < or = k), as do the corresponding single-stage selection procedures which take exactly n observations from each of the k populations. The sequential procedures always require less (often substantially less) than kn observations to terminate experimentation. In the present paper we specialize these procedures, and focus on the particular goal of selecting the population associated with p sub k where p(1) < or =...< or = p(k) are the ordered pi (1 < or = < or = k). These results along with other related ones will assist the potential user of the sequential procedure in assessing its merits relative to those of other competing procedures.