Publication
Title
Comparing computer experiments for the Gaussian process model using integrated prediction variance
Author
Abstract
Space-filling designs are a common choice of experimental design strategy for computer experiments. This article compares space-filling design types based on their theoretical prediction variance properties with respect to the Gaussian process model. An analytical solution for calculating the integrated prediction variance (IV) of the Gaussian process model is given. Using the analytical calculation of IV as a response variable, this article presents a study of the effects of dimension; sample size; value of parameter vector, h; and experimental design type using a factorial design and regression analysis.
Language
English
Source (journal)
Quality engineering
Publication
2013
ISSN
0898-2112
Volume/pages
25:2(2013), p. 164-174
ISI
000315685700007
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
External links
Web of Science
Record
Identification
Creation 06.03.2013
Last edited 03.08.2017
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