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...
Main Authors: | , |
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Corporate Author: | |
Format: | Electronic |
Language: | English |
Published: |
New York, NY :
Springer New York : Imprint: Springer,
2013.
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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.