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Sequential Analysis and Optimal Design

Sequential Analysis and Optimal Design

£35.99

Part of CBMS-NSF Regional Conference Series in Applied Mathematics

  • Date Published: January 1972
  • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • format: Paperback
  • isbn: 9780898710069

£ 35.99
Paperback

This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
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  • An exploration of the interrelated fields of design of experiments and sequential analysis with emphasis on the nature of theoretical statistics and how this relates to the philosophy and practice of statistics.

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    Product details

    • Date Published: January 1972
    • format: Paperback
    • isbn: 9780898710069
    • length: 125 pages
    • dimensions: 255 x 178 x 100 mm
    • weight: 0.3kg
    • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • Table of Contents

    Preliminaries on probability
    Generalities about the conventional theory of design of experiments
    Optimal sample size
    Preliminaries on regression
    Design for linear regression: Elfving's method
    Maximum-likelihood estimation
    Locally optimal designs for estimation
    More design in regression experiments
    Testing hypotheses
    Optimal sample size in testing
    Sequential probability-ratio test
    Optimality of sequential probability-ratio test
    Motivation for an approach to sequential design of experiments in testing hypotheses
    Asymptotic optimality of procedure A in sequential design
    Extensions and open questions in sequential design
    The problem of adjacent hypotheses
    Testing for the sign of a normal mean: no indifference zone
    Bandit problems
    Sequential estimation of a normal mean
    sequential estimation of the common mean of two normal populations.

  • Author

    Herman Chernoff

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