Experimental designs for model discrimination

Friedrich Pukelsheim; James L. Rosenberger

doi:10.1080/01621459.1993.10476317

Experimental designs for model discrimination

Friedrich Pukelsheim, James L. Rosenberger

Statistics

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51 Scopus citations

Abstract

We present designs that perform well for several objectives simultaneously. Three different approaches are discussed: to augment a given design in an optimal way, to evaluate a mixture of the various criteria, and to optimize one objective subject to achieving a prescribed efficiency level for the others. Our sample designs are for the situation of discriminating between a second- and third-degree polynomial fit, under the D-criterion and geometric mixtures of D-criteria.

Original language	English (US)
Pages (from-to)	642-649
Number of pages	8
Journal	Journal of the American Statistical Association
Volume	88
Issue number	422
DOIs	https://doi.org/10.1080/01621459.1993.10476317
State	Published - Jun 1993

All Science Journal Classification (ASJC) codes

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1080/01621459.1993.10476317

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abstract = "We present designs that perform well for several objectives simultaneously. Three different approaches are discussed: to augment a given design in an optimal way, to evaluate a mixture of the various criteria, and to optimize one objective subject to achieving a prescribed efficiency level for the others. Our sample designs are for the situation of discriminating between a second- and third-degree polynomial fit, under the D-criterion and geometric mixtures of D-criteria.",

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Experimental designs for model discrimination

Abstract

All Science Journal Classification (ASJC) codes

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