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Bayes-optimal sequentially planned decision procedures

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Part of the book series: Lecture Notes in Statistics ((LNS,volume 79))

Abstract

In Chapter I we defined (see (1.22)/(1.25)) sequentially planned statistical decision procedures; Chapter III contained some examples of such procedures. In the sequel we consider the construction of ”optimal” procedures for general sequential statistical decision problems

$$P = \left( {\left( {\mathcal{X},\mathcal{B}} \right),\Theta ,{{{\left( {{{P}_{\vartheta }}} \right)}}_{{\vartheta \in A}}}\left( {D,\mathcal{D}} \right),{{{\left( {{{L}_{a}}} \right)}}_{{a \in A{{,}^{C}}}}}} \right) $$

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  1. Using a program due to Lübbert (1988)

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© 1993 Springer-Verlag New York, Inc.

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Schmitz, N. (1993). Bayes-optimal sequentially planned decision procedures. In: Schmitz, N. (eds) Optimal Sequentially Planned Decision Procedures. Lecture Notes in Statistics, vol 79. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2736-6_4

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  • DOI: https://doi.org/10.1007/978-1-4612-2736-6_4

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-97908-3

  • Online ISBN: 978-1-4612-2736-6

  • eBook Packages: Springer Book Archive

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