Accession Number : ADA115653
Title : Closed Adaptive Sequential Procedures for Selecting the Best of k or = 2 Bernoulli Populations.
Descriptive Note : Technical rept.,
Corporate Author : CORNELL UNIV ITHACA NY SCHOOL OF OPERATIONS RESEARCH AND INDUSTRIAL ENGINEERING
Personal Author(s) : Bechhofer,Robert E ; Kulkarni,Radhika V
PDF Url : ADA115653
Report Date : Jul 1981
Pagination or Media Count : 56
Abstract : The goal of selecting that one of k or = 2 Bernoulli populations which has the largest single-trial 'success' orobability is treated. Consideration is restricted to procedures which take no more than n observations from any one of the K populations. One such procedure is the single-stage procedure of Sobel and Huyett (1957) which takes exactly n observations from each of the k population. We propose a one-at-a-time adaptive sampling rule (R*) which when used in conjunction with a particular stopping rule (S*) and terminal decision rule (T*) achieves the same probability of a correct selection as does the single-stage procedure uniformly. The procedure (R*, S*, T*) is generalized for k 2 to accommodate such goals as 'Selecting the s (1 or = s or = k-1) 'best' Bernoulli populations with regard to order,' and is shown to have desirable properties for these goals as well.
Descriptors : *Bernoulli distribution, *Population(Mathematics), *Sequential analysis, Adaptive systems, Limitations, Observation, Sampling, Selection, Probability distribution functions
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE