Abstract
Bechhofer and Kulkarni (1982) proposed procedures for selecting that one of k Bernoulli populations with the largest single-trial success probability. They showed that their procedure for k = 2 minimizes the expected total sample size amongst a class of procedures, all of which attain the same probability of correct selection. Kulkarni and Jennison (1986) generalized this result to the case k'Z 3. In this article we prove the stronger result that the Bechhofer-Kulkami procedure for each k = 2 stochastically minimizes the distribution of sample size amongst procedures in the same class. That is, the distribution of sample size for the Bechhofer-Kulkarni procedure is the same as or stochastically smaller than that for any other procedure in the class.
| Original language | English |
|---|---|
| Pages (from-to) | 281-291 |
| Number of pages | 11 |
| Journal | Sequential Analysis |
| Volume | 8 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1 Jan 1989 |
Bibliographical note
Funding Information:I wish to thank Professor V. G. Kulkarni for proposing the problem considered herein, and Professor R. E. Bechhofer for bringing the problem to my attention. This research was supported in part by U. S. Army Research Office - Durham Contract DAAG-29-81-0168 at Cornell University.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
Funding
I wish to thank Professor V. G. Kulkarni for proposing the problem considered herein, and Professor R. E. Bechhofer for bringing the problem to my attention. This research was supported in part by U. S. Army Research Office - Durham Contract DAAG-29-81-0168 at Cornell University.
Keywords
- adaptive sampling
- k-population Bernoulli selection problem
- sequential selection procedure
ASJC Scopus subject areas
- Statistics and Probability
- Modelling and Simulation