A comparison of different methods for building Bayesian kriging models

Younus Hazim Al-Taweel; Najlaa Sadeek

doi:10.18187/pjsor.v16i1.2921

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Abstract

Kriging is a statistical approach for analyzing computer experiments. Kriging models can be used as fast running surrogate models for computationally expensive computer codes. Kriging models can be built using different methods, the maximum likelihood estimation method and the leave-one-out cross validation method. The objective of this paper is to evaluate and compare these different methods for building kriging models. These evaluation and comparison are achieved via some measures that test the assumptions that are used in building kriging models. We apply kriging models that are built based on the two different methods on a real high dimensional example of a computer code. We demonstrate our evaluation and comparison through some measures on this real computer code.

Keywords

Kriging models Computer codes Maximum likelihood estimation Cross validation Robot Arm function

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Creative Commons Attribution 4.0 International (CC BY 4.0)

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Author Biographies

Younus Hazim Al-Taweel, University of Mosul

Department of Mathematics,Â College of Education for Pure Science

Najlaa Sadeek, University of Mosul

Department of Mathematics,Â College of Education for Pure Science

Publication information

Published: 2020-03-06

Issue: Vol. 16 No. 1, 2020

Pages: 73-82

DOI: 10.18187/pjsor.v16i1.2921

How to Cite

Al-Taweel, Y. H., & Sadeek, N. (2020). A comparison of different methods for building Bayesian kriging models. Pakistan Journal of Statistics and Operation Research, 16(1), 73-82. https://doi.org/10.18187/pjsor.v16i1.2921

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