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Model-oriented design of experiments

Fedorov, V. V.

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Model-oriented design of experiments

Record Type:	Electronic resources : Monograph/item
Title/Author:	Model-oriented design of experiments/ by Valerii V. Fedorov, Peter Hackl.
Author:	Fedorov, V. V.
other author:	Hackl, Peter.
Published:	New York, NY :Springer New York : : 2025.,
Description:	xvi, 131 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Preface -- Introduction -- 1. Some Facts From Regression Analysis -- 2. Convex Design Theory -- 3. Numerical Techniques -- 4. Optimal Design under Constraints -- 5. Special Cases and Applications -- A. Elemental Fisher Information -- B. Selected Formulas from Matrix Theory -- C. List of Symbols -- References -- Index.
Contained By:	Springer Nature eBook
Subject:	Experimental design. -
Online resource:	https://doi.org/10.1007/978-1-0716-4302-0
ISBN:	9781071643020

Model-oriented design of experiments
Fedorov, V. V.

Model-oriented design of experiments[electronic resource] /by Valerii V. Fedorov, Peter Hackl. - Second edition. - New York, NY :Springer New York :2025. - xvi, 131 p. :ill. (some col.), digital ;24 cm. - Lecture notes in statistics,v. 1962197-7186 ;. - Lecture notes in statistics ;v. 196..

Preface -- Introduction -- 1. Some Facts From Regression Analysis -- 2. Convex Design Theory -- 3. Numerical Techniques -- 4. Optimal Design under Constraints -- 5. Special Cases and Applications -- A. Elemental Fisher Information -- B. Selected Formulas from Matrix Theory -- C. List of Symbols -- References -- Index.

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.

ISBN: 9781071643020

Standard No.: 10.1007/978-1-0716-4302-0doiSubjects--Topical Terms:

524737
Experimental design.

LC Class. No.: QA279

Dewey Class. No.: 519.57

Model-oriented design of experiments
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245 1 0 $a Model-oriented design of experiments $h [electronic resource] / $c by Valerii V. Fedorov, Peter Hackl.
250 $a Second edition.
260 $a New York, NY : $b Springer New York : $b Imprint: Springer, $c 2025.
300 $a xvi, 131 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in statistics, $x 2197-7186 ; $v v. 196
505 0 $a Preface -- Introduction -- 1. Some Facts From Regression Analysis -- 2. Convex Design Theory -- 3. Numerical Techniques -- 4. Optimal Design under Constraints -- 5. Special Cases and Applications -- A. Elemental Fisher Information -- B. Selected Formulas from Matrix Theory -- C. List of Symbols -- References -- Index.
520 $a 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.
650 0 $a Experimental design. $3 524737
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950 $a Mathematics and Statistics (SpringerNature-11649)