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Modified Robust Design Criteria for Poisson Mixed Models

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Contemporary Experimental Design, Multivariate Analysis and Data Mining

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Abstract

The maximin D-optimal design (MMD-optimal design) and hypercube design (HCD-optimal design) are two robust designs which overcome the problem of design dependence on the unknown parameters. This article considers the robust designs for Poisson mixed models. Given the prior knowledge of the fixed effects parameters, a modification of the two robust design criteria is proposed by applying the number-theoretic methods. The simulated annealing algorithm is used to find the optimal exact designs. The results show that the modified optimal designs perform better in the relative D-efficiency and programming time.

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Acknowledgments

The work is supported by the NSFC grants 11971318, 11871143.

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Authors and Affiliations

  1. Huaiyin Institute of Technology, Jiangsu, 223003, China

    Hongyan Jiang

  2. College of Mathematics and Science, Shanghai Normal University, Shanghai, 200234, China

    Rongxian Yue

Authors
  1. Hongyan Jiang
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  2. Rongxian Yue
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Corresponding author

Correspondence to Rongxian Yue .

Editor information

Editors and Affiliations

  1. Department of Financial Engineering, Princeton University, Princeton, NJ, USA

    Jianqing Fan

  2. Department of Mathematics, The University of Manchester, Manchester, UK

    Jianxin Pan

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Jiang, H., Yue, R. (2020). Modified Robust Design Criteria for Poisson Mixed Models. In: Fan, J., Pan, J. (eds) Contemporary Experimental Design, Multivariate Analysis and Data Mining. Springer, Cham. https://doi.org/10.1007/978-3-030-46161-4_9

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