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Article
2023
Computational aspects of experimental designs in multiple-group mixed models
Computational aspects of experimental designs in multiple-group mixed models
Abstract (English)
We extend the equivariance and invariance conditions for construction of optimal designs to multiple-group mixed models and, hence, derive the support of optimal designs for first- and second-order models on a symmetric square. Moreover, we provide a tool for computation of D - and L -efficient exact designs in multiple-group mixed models by adapting the algorithm of Harman et al. (Appl Stoch Models Bus Ind, 32:3–17, 2016). We show that this algorithm can be used both for size-constrained problems and also in settings that require multiple resource constraints on the design, such as cost constraints or marginal constraints.
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Statistical papers, 65 (2023), 2, 865-886.
https://doi.org/10.1007/s00362-023-01416-1.
ISSN: 1613-9798
ISSN: 0932-5026
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Prus, M., & Filová, L. (2023). Computational aspects of experimental designs in multiple-group mixed models. Statistical papers, 65(2). https://doi.org/10.1007/s00362-023-01416-1
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English
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@article{Prus2023,
doi = {10.1007/s00362-023-01416-1},
author = {Prus, Maryna and Filová, Lenka},
title = {Computational aspects of experimental designs in multiple-group mixed models},
journal = {Statistical papers},
year = {2023},
volume = {65},
number = {2},
pages = {865--886},
}