The quasi-fiducial model selection for Kriging model
Chen Fan,
Shuqin Zhang and
Xinmin Li
Statistical Theory and Related Fields, 2025, vol. 9, issue 3, 285-296
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.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/24754269.2025.2537484 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tstfxx:v:9:y:2025:i:3:p:285-296
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tstf20
DOI: 10.1080/24754269.2025.2537484
Access Statistics for this article
Statistical Theory and Related Fields is currently edited by Zhao Wei
More articles in Statistical Theory and Related Fields from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().