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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Pronzato, Luc (Autor), Pázman, Andrej (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Colección:Lecture Notes in Statistics, 212
Temas:
Biometry.
Statistics .
Social sciences-Statistical methods.
Biostatistics.
Statistics.
Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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