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NPUA: A new approach for the analysis of computer experiments

Dette, H. and Pepelyshev, Andrey ORCID: 2010. NPUA: A new approach for the analysis of computer experiments. Chemometrics and Intelligent Laboratory Systems 104 (2) , pp. 333-340. 10.1016/j.chemolab.2010.10.001

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An important problem in the analysis of computer experiments is the specification of the uncertainty of the prediction according to a meta-model. The Bayesian approach, developed for the uncertainty analysis of deterministic computer models, expresses uncertainty by the use of a Gaussian process. There are several versions of the Bayesian approach, which are different in many regards but all of them lead to time consuming computations for large data sets. In the present paper we introduce a new approach in which the distribution of uncertainty is obtained in a general nonparametric form. The proposed approach is called non-parametric uncertainty analysis (NPUA), which is computationally simple since it combines generic sampling and regression techniques. We compare NPUA with the Bayesian and Kriging approaches and show the advantages of NPUA for finding points for the next runs by reanalyzing the ASET model.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Mathematics
Subjects: Q Science > QA Mathematics
Uncontrolled Keywords: Computer experiments; Uncertainty analysis; Importance sampling; Stepwise regression; The jackknife technique; Sequential designs
Publisher: Elsevier
ISSN: 0169-7439
Last Modified: 24 Oct 2022 11:42

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