Model-Oriented Design of Experiments (Lecture Notes in Statistics, 125)

Fedorov, Valerii V.,Hackl, Peter

ISBN 10: 0387982159 / ISBN 13: 9780387982151

Published by Springer, 1997

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Bibliographic Details

• Title: Model-Oriented Design of Experiments (Lecture Notes in Statistics, 125)
• Publisher: Springer
• Publication Date: 1997
• Language: English
• ISBN 10: 0387982159
• ISBN 13: 9780387982151
• Binding: paperback
• Condition: Good

About this title

Synopsis

Here, the authors explain the basic ideas so as to generate interest in modern problems of experimental design. The topics discussed include designs for inference based on nonlinear models, designs for models with random parameters and stochastic processes, designs for model discrimination and incorrectly specified (contaminated) models, as well as examples of designs in functional spaces. Since the authors avoid technical details, the book assumes only a moderate background in calculus, matrix algebra, and statistics. However, at many places, hints are given as to how readers may enhance and adopt the basic ideas for advanced problems or applications. This allows the book to be used for courses at different levels, as well as serving as a useful reference for graduate students and researchers in statistics and engineering.

Synopsis

This is author-approved bcc: Optimal design of experiments is an essential component of any research that aims at the estimation of unknown parameters, at model validation, or the comparison and selection of the best among several competing models. The authors' goals are to explain the basic ideas and to create interest in modern problems of experimental design. The topics discussed include designs for inference based on nonlinear models, designs for models with random parameters and stochastic processes, designs for model discrimination and incorrectly specified (contaminated) models, and examples of designs in functional spaces. As the authors avoid technical details, the book assumes only a moderate background in calculus, matrix algebra, and statistics. However, at many places, hints are given how the reader may enhance and adopt the basic ideas for advanced problems or applications. This will allow the book to be used for courses at different levels, and it will be a useful reference for graduate students and researchers in statistics and engineering. Valerii V. Fedorov is Senior Reseacher at Oak Ridge National Laboratory and author of "The Theory of Optimal Experiments."

Peter Hackl is Professor of Statistics at the University of Economics and Business Administration in Vienna, Austria, and President of the Austrian Statistical Society.