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Optimum Experimental Designs

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Breakthroughs in Statistics

Part of the book series: Springer Series in Statistics ((PSS))

Summary

After some introductory remarks, we discuss certain basic considerations such as the nonoptimality of the classical symmetric (balanced) designs for hypothesis testing, the optimality of designs invariant under an appropriate group of transformations, etc. In section 3 we discuss complete classes of designs, while in section 4 we consider methods for verifying that designs satisfy certain specific optimality criteria, or for computing designs which satisfy such criteria. Some of the results are new, while part of the paper reviews pertinent results of the author and others.

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Author information

Authors and Affiliations

  1. Cornell and Oxford Universities, UK

    J. C. Kiefer

Authors
  1. J. C. Kiefer
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Editor information

Editors and Affiliations

  1. College of Business and Management, University of Maryland at College Park, College Park, MD, 20742, USA

    Samuel Kotz

  2. Department of Statistics Phillips Hall, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA

    Norman L. Johnson

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© 1992 Springer Science+Business Media New York

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Kiefer, J.C. (1992). Optimum Experimental Designs. In: Kotz, S., Johnson, N.L. (eds) Breakthroughs in Statistics. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-0919-5_28

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  • DOI: https://doi.org/10.1007/978-1-4612-0919-5_28

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-94037-3

  • Online ISBN: 978-1-4612-0919-5

  • eBook Packages: Springer Book Archive

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