Model-Oriented Design of Experiments: 209 Second Edition 2025 Edition

Model-Oriented Design of Experiments: 209 Second Edition 2025 Edition book cover

Model-Oriented Design of Experiments: 209 Second Edition 2025 Edition

Author(s): Valerii V. Fedorov (Author), Peter Hackl (Author)

  • Publisher: Springer
  • Publication Date: 27 Dec. 2024
  • Edition: Second Edition 2025
  • Language: English
  • Print length: 147 pages
  • ISBN-10: 1071643010
  • ISBN-13: 9781071643013

Book Description

This book presents the basic ideas of statistical methods in the design of optimal experiments. This new edition now includes sections on design techniques based on the elemental Fisher information matrices (as opposed to Pearson information/moment matrices), allowing a seamless extension of the design techniques to inferential problems where the shape of distributions is essential for optimal design construction. Topics include designs for nonlinear models, models with random parameters and models with correlated observations, designs for model discrimination and misspecified (contaminated) models, and designs in functional spaces.

The authors avoid technical details, assuming a moderate background in calculus, matrix algebra, and statistics. In many places, however, suggestions are made as to how the ideas presented in this book can be extended and elaborated for use in real scientific research and practical engineering problems.

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From the Back Cover

This book presents the basic ideas of statistical methods in the design of optimal experiments. This new edition now includes sections on design techniques based on the elemental Fisher information matrices (as opposed to Pearson information/moment matrices), allowing a seamless extension of the design techniques to inferential problems where the shape of distributions is essential for optimal design construction. Topics include designs for nonlinear models, models with random parameters and models with correlated observations, designs for model discrimination and misspecified (contaminated) models, and designs in functional spaces.

The authors avoid technical details, assuming a moderate background in calculus, matrix algebra, and statistics. In many places, however, suggestions are made as to how the ideas presented in this book can be extended and elaborated for use in real scientific research and practical engineering problems.

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