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Minimax Versus Robust Experimental Design: Two Simple Examples

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Robustness of Statistical Methods and Nonparametric Statistics

Part of the book series: Theory and Decision Library ((TDLB,volume 1))

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Abstract

There exist many approaches to assessing robustness of statistical procedures. We discuss two of them: one connected with stability of the performance of a given statistic when passing to a supermodel, and the second connected with constructing the procedure which is minimax in the supermodel. Both approaches are compared in simple practical situations.

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References

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Author information

Authors and Affiliations

  1. Institute of Mathematics, Polish Academy of Sciences, Warsaw, Poland

    Ryszard Zieliński

Authors
  1. Ryszard Zieliński
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Editor information

Editors and Affiliations

  1. Mathematical Department of Wilhelm Pieck University, Rostock, Germany

    Dieter Rasch

  2. Research Centre of Animal Production Dummerstorf-Rostock of the Academy of Agricultural Sciences of the GDR, Rostock, Germany

    Dieter Rasch

  3. Department of Statistics, McMaster University, Hamilton, Ontario, Canada

    Moti Lal Tiku

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© 1984 Academy of Agricultural Sciences of the GDR, Research Centre of Animal Production, Dummerstorf-Rostock, DDR 2551 Dummerstorf.

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Zieliński, R. (1984). Minimax Versus Robust Experimental Design: Two Simple Examples. In: Rasch, D., Tiku, M.L. (eds) Robustness of Statistical Methods and Nonparametric Statistics. Theory and Decision Library, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-6528-7_39

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  • DOI: https://doi.org/10.1007/978-94-009-6528-7_39

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-009-6530-0

  • Online ISBN: 978-94-009-6528-7

  • eBook Packages: Springer Book Archive

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