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Optimal designs for prediction in random coefficient regression with one observation per individual

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  • Maryna Prus

    (University of Hohenheim
    Linköping University)

Abstract

The subject of this work is random coefficient regression models with only one observation per observational unit (individual). An analytical solution in form of optimality conditions is proposed for optimal designs for the prediction of individual random effect for a group of selected individuals. The behavior of optimal designs is illustrated by the example of linear regression models.

Suggested Citation

  • Maryna Prus, 2023. "Optimal designs for prediction in random coefficient regression with one observation per individual," Statistical Papers, Springer, vol. 64(4), pages 1057-1068, August.
    • Handle: RePEc:spr:stpapr:v:64:y:2023:i:4:d:10.1007_s00362-023-01440-1
    DOI: 10.1007/s00362-023-01440-1
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    References listed on IDEAS

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    1. Maryna Prus & Rainer Schwabe, 2016. "Optimal designs for the prediction of individual parameters in hierarchical models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 175-191, January.
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