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A stochastic characterization of Loewner optimality design criterion in linear models |
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| Authors: | Erkki P. Liski Alexander Zaigraev |
| Affiliation: | (1) Department of Mathematics, Statistics and Philosophy, University of Tampere, P.O. BOX 607, FIN-33101 Tampere, Finland (e-mail: epl@uta.fi), FI;(2) Faculty of Mathematics and Computer Science, Nicholas Copernicus University, Chopin str. 12/18, PL-87-100 Torun, Poland, PL |
| Abstract: | In this paper we present a new stochastic characterization of the Loewner optimality design criterion. The result is obtained by proving a generalization to the well known corollary of Anderson's theorem. Certain connections between the Loewner optimality and the stochastic distance optimality design criterion are showed. We also present applications and generalizations of the main result. Received: 9 August 2000 |
| Keywords: | : Anderson's theorem stochastic convex and distance optimality criteria Kiefer optimality admissibility information equivalence multifactor first degree polynomial models orthogonal and simplex designs |
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