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Design of experiments in nonlinear m...

Pázman, Andrej.

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

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Design of experiments in nonlinear models :Luc Pronzato, Andrej Pázman.
Reminder of title:	asymptotic normality, optimality criteria and small-sample properties /
Author:	Pronzato, Luc,
other author:	Pázman, Andrej.
Published:	New York :Springer,c2013.
Description:	xv, 399 p. :ill. (some col.) ;24 cm.
Subject:	Asymptotic efficiencies (Statistics)
ISBN:	1461463629 (pbk.) :

Design of experiments in nonlinear models :asymptotic normality, optimality criteria and small-sample properties /
Pronzato, Luc,1959-

Design of experiments in nonlinear models :asymptotic normality, optimality criteria and small-sample properties /Luc Pronzato, Andrej Pázman. - New York :Springer,c2013. - xv, 399 p. :ill. (some col.) ;24 cm. - Lecture notes in statistics,v. 2120930-0325 ;. - Lecture notes in statistics (Springer-Verlag) ;v. 119..

Includes bibliographical references (p. 369-387) and indexes.

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.

ISBN: 1461463629 (pbk.) :NT$3489

LCCN: 2013932292Subjects--Topical Terms:

715176
Asymptotic efficiencies (Statistics)

LC Class. No.: QA279 / .P748 2013

Dewey Class. No.: 001.4/22

Design of experiments in nonlinear models :asymptotic normality, optimality criteria and small-sample properties /
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245 1 0 $a Design of experiments in nonlinear models : $b asymptotic normality, optimality criteria and small-sample properties / $c Luc Pronzato, Andrej Pázman.
260 $a New York : $b Springer, $c c2013.
300 $a xv, 399 p. : $b ill. (some col.) ; $c 24 cm.
490 1 $a Lecture notes in statistics, $x 0930-0325 ; $v v. 212
504 $a Includes bibliographical references (p. 369-387) and indexes.
505 0 $a 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.
650 0 $a Asymptotic efficiencies (Statistics) $3 715176
650 0 $a Experimental design. $3 181887
650 0 $a Nonlinear theories. $3 182014
650 0 $a Regression analysis. $3 181872
700 1 $a Pázman, Andrej. $3 715175
830 0 $a Lecture notes in statistics (Springer-Verlag) ; $v v. 119. $3 434505