Optimal Sequentially Planned Decision Procedures (Lecture Notes in Statistics, 79) - Primera edición

EAN (ISBN-13): 9780387979083
ISBN (ISBN-10): 0387979085
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Año de publicación: 1992
Editorial: Springer New York

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ISBN/EAN: 0387979085

ISBN - escritura alterna:
0-387-97908-5, 978-0-387-97908-3
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Autor del libro: norbert schmitz, duscha, lübbert, norbert thomas, eke norbert, rise
Título del libro: optimal, procedures, decision

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Datos del la editorial

Autor: Norbert Schmitz
Título: Lecture Notes in Statistics; Optimal Sequentially Planned Decision Procedures
Editorial: Springer; Springer US
207 Páginas
Año de publicación: 1992-10-28
New York; NY; US
Idioma: Inglés
106,99 € (DE)
109,99 € (AT)
118,00 CHF (CH)
Available
XII, 207 p.

BC; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Hypothese; Power; Sequential Probability Ratio Test; probability; Probability Theory; Stochastik; EA

I. Introduction.- § 1 Sequential statistical procedures.- § 2 Objectives of sequential analysis.- § 3 Historical remarks on the development of sequential analysis.- § 4 Examples of sequential procedures; purely sequential statistical decision procedures.- § 5 Objections to purely sequential statistical decision procedures.- § 6 Sequentially planned statistical procedures.- II. Optimal sequential sampling plans.- § 1 Problems of optimal sampling.- § 2 Optimal sampling plans for finite horizon.- § 3 Existence of optimal sampling plans for general A.- § 4 Optimal sampling plans for the Markov case.- III. Sequentially planned tests; sequentially planned probability ratio tests.- § 1 Notation.- § 2 The iid case.- § 3 Sequentially planned probability ratio tests.- § 4 Algorithms for computing the OC- and ASC-function of SPPRT’s in the iid case.- § 5 Remarks on the implementation of the algorithms; Examples.- § 6 Remarks on the comparison of the methods and on convergence-improvements for the BF-/EV- method.- IV. Bayes-optimal sequentially planned decision procedures.- § 1 Introduction.- § 2 Bayes-procedures.- § 3 A posteriori-distributions.- § 4 Bayes-optimal sampling plans; Markov case.- V. Optimal sequentially planned tests under side conditions.- § 1 Decision problems with side conditions.- § 2 Characterizations of optimal sequentially planned decision procedures.- § 3 Sequentially planned tests for simple hypotheses in the iid case.- § 4 The modified Kiefer-Weiss problem in the iid case.- § 5 Locally optimal sequentially planned tests in the dominated iid case.- § 6 Remarks on the monotonicity of the power functions of SPPRT’s and GSPPRT’s.- Appendix A: Mathematical models for sequentially planned sampling procedures.- § A.1 The concept ofpolicies by Mandelbaum and Vanderbei.- § A.2 The concept of tactics by Krengel and Sucheston.- § A.3 The concept of decision functions by Washburn and Willsky.- § A.4 The concept of stopped decision models by Rieder.- Appendix B: Implementation of the algorithms EV, BF and ILE; Diophantine Approximation.- § B.1 Listing of the modules.- § B.2 Diophantine approximation.- Appendix C: References, Bibliography.