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Optimal sequential sampling plans

  • Norbert Schmitz
Part of the Lecture Notes in Statistics book series (LNS, volume 79)

Abstract

Statistical decision procedures where the sizes of sub-samples are determined sequentially (sequentially planned statistical decision procedures) are described in definition (1.22) by a sequential plan r and a terminal decision procedure ε. I.e. similarly to purely sequential decision procedures (see definition (1.12)) such a procedure is split up into
  • - a part τ which is focused upon the sequential determinations of sub-samples and

  • - a part ϕ = (ϕ a )a∈A which exclusively concerns the terminal decisions.

Keywords

Decision Procedure Sampling Plan Optimal Sampling Transition Kernel Finite Horizon 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 22.
    There is no relation to the admissibility concept of decision theory; existence only of the expected value in the wide sense is assumed, i.e. EZ+ < ∞ or EZ- < ∞.Google Scholar
  2. 23.
    This assumption is e.g. fulfilled if Za ≤ 0 (i.e. allow an interpretation as losses); comp. Chapter 4.Google Scholar
  3. 24.
    We always define supθ … = maxθ… =-∞.Google Scholar

Copyright information

© Springer-Verlag New York, Inc. 1993

Authors and Affiliations

  • Norbert Schmitz
    • 1
  1. 1.Institut für Mathematische StatistikWestfälische Wilhelms-Universität MünsterMünster/W.Germany

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