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A comparison of different methods for building Bayesian kriging models
Author(s):
1. Younus Al-Taweel: Department of Mathematics, College of Education for Pure Science, University of Mosul, Iraq
2. Najlaa Sadeek: Department of Mathematics, College of Education for Pure Science, University of Mosul, Iraq
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 evaluations and comparisons 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. 
Page(s): 73-82
Published: Journal: Pakistan Journal of Statistics and Operation Research, Volume: 16, Issue: 1, Year: 2020
Keywords:
maximum likelihood estimation , cross validation , Robot Arm function , Kriging models , Computer codes
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