Design of Experiments in Nonlinear Models Asymptotic Normality, Optimality Criteria and Small-Sample Properties /

• Κύριοι συγγραφείς: Pronzato, Luc (Συγγραφέας), Pázman, Andrej (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York : Imprint: Springer, 2013.
• Σειρά: Lecture Notes in Statistics, 212
• Θέματα: Statistics.; Statistics for Life Sciences, Medicine, Health Sciences.; Statistics, general.; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.

Design of Experiments in Nonlinear Models: Asymptotic Normality, Optimality Criteria and Small-Sample Properties provides a comprehensive coverage of the various aspects of experimental design for nonlinear models. The book contains original contributions to the theory of optimal experiments that wi...

Πίνακας περιεχομένων:

• Introduction
• Asymptotic designs and uniform convergence. Asymptotic properties of the LS estimator
• Asymptotic properties of M, ML and maximum a posteriori estimators
• Local optimality criteria based on asymptotic normality
• Criteria based on the small-sample precision of the LS estimator
• Identifiability, estimability and extended optimality criteria
• Nonlocal optimum design
• Algorithms—a survey
• Subdifferentials and subgradients
• Computation of derivatives through sensitivity functions
• Proofs
• Symbols and notation
• List of labeled assumptions
• References.