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Optimal designs in multivariate linear models

Author

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  • Markiewicz, A.
  • Szczepanska, A.

Abstract

The purpose of this paper is to study optimality of an experimental design under the multivariate models with a known or unknown dispersion matrix. In the case of unknown dispersion matrix optimality is considered with respect to the precision in maximum likelihood estimation. We show relations between optimality of designs in univariate models and in their multivariate extensions.

Suggested Citation

  • Markiewicz, A. & Szczepanska, A., 2007. "Optimal designs in multivariate linear models," Statistics & Probability Letters, Elsevier, vol. 77(4), pages 426-430, February.
    • Handle: RePEc:eee:stapro:v:77:y:2007:i:4:p:426-430
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    References listed on IDEAS

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    1. Markiewicz, Augustyn, 2001. "On dependence structures preserving optimality," Statistics & Probability Letters, Elsevier, vol. 53(4), pages 415-419, July.
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    Cited by:

    1. Kleijnen, Jack P.C., 2017. "Regression and Kriging metamodels with their experimental designs in simulation: A review," European Journal of Operational Research, Elsevier, vol. 256(1), pages 1-16.
    2. Katarzyna Filipiak & Augustyn Markiewicz & Anna Szczepańska, 2009. "Optimal designs under a multivariate linear model with additional nuisance parameters," Statistical Papers, Springer, vol. 50(4), pages 761-778, August.

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