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Optimal Model Average Prediction in Orthogonal Kriging Models

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Abstract

The main objective of this paper is to consider model averaging methods for kriging models. This paper proposes a Mallows model averaging procedure for the orthogonal kriging model and demonstrate the asymptotic optimality of the model averaging estimators in terms of mean square error. Simulation studies are conducted to evaluate the performance of the proposed method and compare it with the competitors to demonstrate its superiority. The authors also analyse a real dataset for an illustration.

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Authors and Affiliations

  1. School of Mathematics and Statistics, Qingdao University, Qingdao, 266071, China

    Jun Wang, Jiabei He & Xinmin Li

  2. Department of Statistics, George Washington University, Washington DC, 20052, USA

    Hua Liang

Authors
  1. Jun Wang
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  2. Jiabei He
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  3. Hua Liang
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  4. Xinmin Li
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Corresponding author

Correspondence to Xinmin Li.

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The authors declare no conflict of interest.

Additional information

This research was supported by the National Natural Science Foundation of China under Grant No. 11871294.

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Wang, J., He, J., Liang, H. et al. Optimal Model Average Prediction in Orthogonal Kriging Models. J Syst Sci Complex 37, 1080–1099 (2024). https://doi.org/10.1007/s11424-024-2333-y

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  • DOI: https://doi.org/10.1007/s11424-024-2333-y

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