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

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...

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Bibliographic Details
Main Authors: Pronzato, Luc. (Author), Pz̀man, Andrej. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 2013.
Series:Lecture Notes in Statistics, 212
Subjects:
Online Access:https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4614-6363-4
Table of Contents:
  • 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<U+0014>a survey
  • Subdifferentials and subgradients
  • Computation of derivatives through sensitivity functions
  • Proofs
  • Symbols and notation
  • List of labeled assumptions
  • References.