An adaptive sequential design for model discrimination and parameter estimation in non-linear nested models

C. Tommasi; C. May

doi:10.1063/1.3498294

An adaptive sequential design for model discrimination and parameter estimation in non-linear nested models

C. Tommasi, C. May

Dipartimento di Studi per l'Economia e l'Impresa

Risultato della ricerca: Contributo su rivista › Articolo da conferenza › peer review

Abstract

The DKL-optimality criterion has been recently proposed for the dual problem of model discrimination and parameter estimation, for the case of two rival models. A sequential version of the DKL-optimality criterion is herein proposed in order to discriminate and efficiently estimate more than two nested non-linear models. Our sequential method is inspired by the procedure of Biswas and Chaudhuri (2002), which is however useful only in the set up of nested linear models.

Lingua originale	Inglese
pagine (da-a)	1917-1920
Numero di pagine	4
Rivista	AIP Conference Proceedings
Volume	1281
DOI	https://doi.org/10.1063/1.3498294
Stato di pubblicazione	Pubblicato - 2010
Evento	International Conference on Numerical Analysis and Applied Mathematics 2010, ICNAAM-2010 - Rhodes, Greece Durata: 19 set 2010 → 25 set 2010

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10.1063/1.3498294

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KW - KL-optimality

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An adaptive sequential design for model discrimination and parameter estimation in non-linear nested models

Abstract

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