Generation of optimal designs for nonlinear models when the design points are incidental parameters

Martijn P.F. Berger

doi:10.1007/978-3-642-48678-4

Generation of optimal designs for nonlinear models when the design points are incidental parameters

Martijn P.F. Berger

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

Abstract

This paper considers the problem of finding D-optimal designs for nonlinear exponential models when the design points are not known, and have to be approximated or estimated. The procedure in this paper not only deals with this problem, but also handles the problem that for nonlinear models the information of the parameters is a function of the values of these parameters. The results will be discussed and illustrated for item response theory models that are frequently used in psychometric research.

Original language	English
Title of host publication	Computational statistics
Editors	Yadolah Dodge, Joe Whittaker
Place of Publication	Heidelberg
Publisher	Physica-Verlag
Pages	202-208
Number of pages	7
Volume	2: Proceedings of the 10th Symposium on Computational Statistics, COMPSTAT, Neuchâtel, Switzerland, August 1992
ISBN (Electronic)	978-3-642-48678-4
ISBN (Print)	978-3-642-48680-7
DOIs	https://doi.org/10.1007/978-3-642-48678-4
Publication status	Published - 1992
Event	10th Symposium on Computational Statistics, COMPSTAT 1992 - Neuchâtel, Switzerland Duration: 24 Aug 1992 → 28 Aug 1992 Conference number: 10

Conference

Conference	10th Symposium on Computational Statistics, COMPSTAT 1992
Abbreviated title	COMPSTAT
Country/Territory	Switzerland
City	Neuchâtel
Period	24/08/92 → 28/08/92

Keywords

Rang
Statistical computing
Neural networks
Statistics

Access to Document

10.1007/978-3-642-48678-4

Cite this

Berger, M. P. F. (1992). Generation of optimal designs for nonlinear models when the design points are incidental parameters. In Y. Dodge, & J. Whittaker (Eds.), Computational statistics (Vol. 2: Proceedings of the 10th Symposium on Computational Statistics, COMPSTAT, Neuchâtel, Switzerland, August 1992, pp. 202-208). Physica-Verlag. https://doi.org/10.1007/978-3-642-48678-4

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title = "Generation of optimal designs for nonlinear models when the design points are incidental parameters",

abstract = "This paper considers the problem of finding D-optimal designs for nonlinear exponential models when the design points are not known, and have to be approximated or estimated. The procedure in this paper not only deals with this problem, but also handles the problem that for nonlinear models the information of the parameters is a function of the values of these parameters. The results will be discussed and illustrated for item response theory models that are frequently used in psychometric research.",

keywords = "Rang, Statistical computing, Neural networks, Statistics",

author = "Berger, \{Martijn P.F.\}",

year = "1992",

doi = "10.1007/978-3-642-48678-4",

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volume = "2: Proceedings of the 10th Symposium on Computational Statistics, COMPSTAT, Neuch{\^a}tel, Switzerland, August 1992",

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editor = "Yadolah Dodge and Joe Whittaker",

booktitle = "Computational statistics",

publisher = "Physica-Verlag",

address = "Germany",

note = "10th Symposium on Computational Statistics, COMPSTAT 1992, COMPSTAT ; Conference date: 24-08-1992 Through 28-08-1992",

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Berger, MPF 1992, Generation of optimal designs for nonlinear models when the design points are incidental parameters. in Y Dodge & J Whittaker (eds), Computational statistics. vol. 2: Proceedings of the 10th Symposium on Computational Statistics, COMPSTAT, Neuchâtel, Switzerland, August 1992, Physica-Verlag, Heidelberg, pp. 202-208, 10th Symposium on Computational Statistics, COMPSTAT 1992, Neuchâtel, Switzerland, 24/08/92. https://doi.org/10.1007/978-3-642-48678-4

Generation of optimal designs for nonlinear models when the design points are incidental parameters. / Berger, Martijn P.F.
Computational statistics. ed. / Yadolah Dodge; Joe Whittaker. Vol. 2: Proceedings of the 10th Symposium on Computational Statistics, COMPSTAT, Neuchâtel, Switzerland, August 1992 Heidelberg: Physica-Verlag, 1992. p. 202-208.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

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T1 - Generation of optimal designs for nonlinear models when the design points are incidental parameters

AU - Berger, Martijn P.F.

N1 - Conference code: 10

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N2 - This paper considers the problem of finding D-optimal designs for nonlinear exponential models when the design points are not known, and have to be approximated or estimated. The procedure in this paper not only deals with this problem, but also handles the problem that for nonlinear models the information of the parameters is a function of the values of these parameters. The results will be discussed and illustrated for item response theory models that are frequently used in psychometric research.

AB - This paper considers the problem of finding D-optimal designs for nonlinear exponential models when the design points are not known, and have to be approximated or estimated. The procedure in this paper not only deals with this problem, but also handles the problem that for nonlinear models the information of the parameters is a function of the values of these parameters. The results will be discussed and illustrated for item response theory models that are frequently used in psychometric research.

KW - Rang

KW - Statistical computing

KW - Neural networks

KW - Statistics

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DO - 10.1007/978-3-642-48678-4

M3 - Chapter

SN - 978-3-642-48680-7

VL - 2: Proceedings of the 10th Symposium on Computational Statistics, COMPSTAT, Neuchâtel, Switzerland, August 1992

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BT - Computational statistics

A2 - Dodge, Yadolah

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PB - Physica-Verlag

CY - Heidelberg

T2 - 10th Symposium on Computational Statistics, COMPSTAT 1992

Y2 - 24 August 1992 through 28 August 1992

ER -

Generation of optimal designs for nonlinear models when the design points are incidental parameters

Abstract

Conference

Keywords

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