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The quasi-fiducial model selection for Kriging model

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  • Chen Fan
  • Shuqin Zhang
  • Xinmin Li

Abstract

Kriging models are widely employed due to their simplicity and flexibility in a variety of fields. To gain more distributional information about the unknown parameters, we focus on constructing the fiducial distribution of Kriging model parameters. To solve the challenge of constructing the fiducial marginal distribution for the spatially related parameter, we substitute the Bayesian posterior distribution for the fiducial distribution of this spatially related parameter and present a quasi-fiducial distribution for Kriging model parameters. A Gibbs sampling algorithm is given to get the samples of the quasi-fiducial distribution. Then a model selection criterion based on the quasi-fiducial distribution is proposed. Numerical studies demonstrate that the proposed method is superior to the Lasso and Elastic Net.

Suggested Citation

  • Chen Fan & Shuqin Zhang & Xinmin Li, 2025. "The quasi-fiducial model selection for Kriging model," Statistical Theory and Related Fields, Taylor & Francis Journals, vol. 9(3), pages 285-296, July.
    • Handle: RePEc:taf:tstfxx:v:9:y:2025:i:3:p:285-296
    DOI: 10.1080/24754269.2025.2537484
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