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Design of experiments in nonlinear models : asymptotic normality, optimality criteria and small-sample properties

Auteur: Luc Pronzato; Andrej Pázman
Uitgever: New York, NY : Springer, ©2013.
Serie: Lecture notes in statistics (Springer-Verlag), v.212.
Editie/Formaat:   eBoek : Document : EngelsAlle edities en materiaalsoorten bekijken.
Database:WorldCat
Samenvatting:
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 will interest students and researchers in the field. Practitionners motivated by applications will find valuable tools to  Meer lezen...
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Genre/Vorm: Electronic books
Genre: Document, Internetbron
Soort document: Internetbron, Computerbestand
Alle auteurs / medewerkers: Luc Pronzato; Andrej Pázman
ISBN: 9781461463634 1461463637
OCLC-nummer: 840485712
Beschrijving: 1 online resource.
Inhoud: 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.
Serietitel: Lecture notes in statistics (Springer-Verlag), v.212.
Verantwoordelijkheid: Luc Pronzato, Andrej Pázman.
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This book thoroughly explores connections between the asymptotic properties of estimators in parametric models and experimental design, focused on the estimation of a nonlinear function of the model  Meer lezen...

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