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Efficient lack of fit designs that are optimal to estimate the highest coefficient of a polynomial

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Bischoff, Wolfgang ; Miller, Frank:
Efficient lack of fit designs that are optimal to estimate the highest coefficient of a polynomial.
In: Journal of statistical planning and inference. 136 (2006). - S. 4239-4249.
ISSN 0378-3758

Kurzfassung/Abstract

To check regression models, the authors [Optimal designs which are efficient for lack of fit tests. Ann. Stat., to appear; see also J. Stat. Plann. Inference 136, No. 12, 4239--4249 (2006; Zbl 1098.62098)] introduced optimal designs to estimate a parameter in the class of designs which guarantee a certain efficiency with respect to the power of a lack of fit (LOF-) test. One part of such an optimal design is absolutely continuous with respect to the Lebesgue measure and the other part consists of a finite number of mass points. The optimal design to estimate the highest coefficient of a polynomial regression of fixed degree $k-1$ $(\bold e_{k}$-optimal design) in the class of designs with LOF-efficiency of at least $r$ has the same mass points as the classical $\bold e_{k}$-optimal design if $r$ is small enough. We investigate the set of efficiencies $r$ with that property.

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Publikationsform:Artikel
Schlagwörter:polynomial regression model; efficient designs for lack of fit tests; efficient $\bold e_k$-optimal designs
Institutionen der Universität:Mathematisch-Geographische Fakultät > Mathematik > Lehrstuhl für Mathematik - Statistik und Stochastik
Peer-Review-Journal:Ja
Verlag:North-Holland Publ. Co.
Die Zeitschrift ist nachgewiesen in:
Titel an der KU entstanden:Ja
KU.edoc-ID:2754
Eingestellt am: 23. Sep 2009 10:41
Letzte Änderung: 01. Feb 2010 11:26
URL zu dieser Anzeige: https://edoc.ku.de/id/eprint/2754/
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