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Model-Oriented Design of Experiments de Peter Hackl

Model-Oriented Design of Experiments: Lecture Notes in Statistics

Autor Peter Hackl, Valerii V. Fedorov
en Limba Engleză Paperback – 27 dec 2024
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.
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Specificații

ISBN-13: 9781071643013
ISBN-10: 1071643010
Pagini: 152
Dimensiuni: 155 x 235 x 9 mm
Greutate: 0.24 kg
Ediția:Second Edition 2025
Editura: Springer
Seria Lecture Notes in Statistics

Cuprins

1 Some Facts From Regression Analysis.- 1.1 The Linear Model.- 1.2 More about the Information Matrix.- 1.3 Generalized Versions of the Linear Regression Model.- 1.4 Nonlinear Models.- 2 Convex Design Theory.- 2.1 Optimality Criteria.- 2.2 Some Properties of Optimality Criteria.- 2.3 Continuous Optimal Designs.- 2.4 The Sensitivity Function and Equivalence Theorems.- 2.5 Some Examples.- 2.6 Complements.- 3 Numerical Techniques.- 3.1 First Order Algorithm:D-criterion.- 3.2 First Order Algorithm: The General Case.- 3.3 Finite Sample Size.- 4 Optimal Design under Constraints.- 4.1 Cost Constraints.- 4.2 Constraints for Auxiliary Criteria.- 4.3 Directly Constrained Design Measures.- 5 Special Cases and Applications.- 5.1 Designs for Time-Dependent Models.- 5.2 Regression Models with Random Parameters.- 5.3 Mixed Models and Correlated Observations.- 5.4 Design for “Contaminated” Models.- 5.5 Model Discrimination.- 5.6 Nonlinear Regression.- 5.7 Design in Functional. Spaces.- A Some Results from Matrix Algebra.- B List of Symbols.- References.