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On Group Sequential Sampling

Authors: S. Ehrenfeld;

On Group Sequential Sampling

Abstract

Abstract : The paper investigates the problem of choosing between two simple hypothesis, H sub o and H sub l, in terms of independent, identically distributed random variables, when observations can be taken in groups. At any stage in the decision procedure it must be decided whether to stop or take action now or to continue, in which case the size of the next group of observations must be decided upon. The problem is to find an optimal procedure incorporating a stopping, group size (batch) and terminal action rule. It is shown that the optimal stopping rule is of the sequential probability ratio type. The special, but important, situation where the log likelihood can assume only a finite number of integral multiples of a constant, is investigated. It is shown that optimum procedures can be obtained by proper formulation of the problem in terms of Markov sequential decision schemes and solved by linear programming. Finally, a policy improvement type of routine is presented when the stopping rule is specified.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Average
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