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Robust Planning and Analysis of Experiments

  • Book
  • © 1997

Overview

Authors:
  1. Christine H. Müller

    1. Fachbereich Mathematik und Informatik, WE1, Freie Universität Berlin, Berlin, Germany

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Part of the book series: Lecture Notes in Statistics (LNS, volume 124)

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-x
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  2. Efficient Inference for Planned Experiments

    1. Front Matter

      Pages 1-1
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    2. Planned Experiments

      • Christine H. Müller
      Pages 2-9

    3. Efficiency Concepts for Outlier-Free Observations

      • Christine H. Müller
      Pages 10-24

  3. Robust Inference for Planned Experiments

    1. Front Matter

      Pages 25-25
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    2. Smoothness Concepts of Outlier Robustness

      • Christine H. Müller
      Pages 26-47

    3. Robustness Measures: Bias and Breakdown Points

      • Christine H. Müller
      Pages 48-74

    4. Asymptotic Robustness for Shrinking Contamination

      • Christine H. Müller
      Pages 75-97

    5. Robustness of Tests

      • Christine H. Müller
      Pages 98-107

  4. High Robustness and High Efficiency

    1. Front Matter

      Pages 109-109
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    2. High Robustness and High Efficiency of Estimation

      • Christine H. Müller
      Pages 110-142

    3. High Robustness and High Efficiency of Tests

      • Christine H. Müller
      Pages 143-170

    4. High Breakdown Point and High Efficiency

      • Christine H. Müller
      Pages 171-183

    5. Outlook

      • Christine H. Müller
      Pages 184-188

  5. Back Matter

    Pages 189-236
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Keywords

About this book

Author-approved bcc: Robust statistics and the design of experiments are two of the fastest growing fields in contemporary statistics. Up to now, there has been very little overlap between these fields. In robust statistics, robust alternatives to the nonrobust least squares estimator have been developed, while in experimental design, designs for the efficient use of the least square estimator have been developed. This volume is the first to link these two areas by studying the influence of the design on the efficiency and robustness of robust estimators and tests. It shows that robust statistical procedures profit by an appropriate choice of the design and that efficient designs for a robust statistical analysis are more applicable. The classical approaches of experimental design and robust statistics are introduced before the areas are linked. Dr. Christine H. M ller teaches at the Department of Mathematics and Computer Science of the Free University of Berlin and is a member of the research project on "Efficient Experiments in Industrial Production." From 1988-1991, she worked as a biometrician at the Medical Department of the Free University of Berlin.

Authors and Affiliations

  • Fachbereich Mathematik und Informatik, WE1, Freie Universität Berlin, Berlin, Germany

    Christine H. Müller

Bibliographic Information

  • Book Title: Robust Planning and Analysis of Experiments

  • Authors: Christine H. Müller

  • Series Title: Lecture Notes in Statistics

  • DOI: https://doi.org/10.1007/978-1-4612-2296-5

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag New York, Inc. 1997

  • Softcover ISBN: 978-0-387-98223-6Published: 20 June 1997

  • eBook ISBN: 978-1-4612-2296-5Published: 06 December 2012

  • Series ISSN: 0930-0325

  • Series E-ISSN: 2197-7186

  • Edition Number: 1

  • Number of Pages: X, 234

  • Topics: Applications of Mathematics

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