Abstract
Two inverse sampling procedures, one that uses the classical vector-at-a-time observation rule and another that uses the play-the-winner observation rule, are shown to select the best of $k$ binomial populations with the same probability, independent of the probabilities of success. This shows that the play-the-winner rule is better from the point of view that both the sample size and number of failures of each population are stochastically smaller using play-the-winner than vector-at-a-time.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
