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An Investigation of the Relationship Between the Gaussian Process Model Parameters and Surface Area in Three Dimensions
Author(s) -
Silvestrini Rachel T.,
Silvestrini Anthony C.
Publication year - 2016
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.1757
Subject(s) - kriging , gaussian process , gaussian , measure (data warehouse) , surface (topology) , mathematics , surface roughness , process (computing) , statistics , gaussian network model , statistical physics , computer science , data mining , geometry , physics , quantum mechanics , operating system
In this paper, we study the relationship between the fitted parameters in a Gaussian process (kriging) model and the complexity of the resulting response surface. This study is done for models with one response and two input variables. An analytical calculation of surface roughness is used as a measure of the complexity of the response surface fit by the Gaussian process model. Our findings indicate that the size of the fitted model parameters as measured across different fits and data sets do not give indication as to the complexity of the surface. We do, however, show that the magnitude of each of the parameters in a single fitted model gives indication about the amount of variability in the direction of that fitted parameter. Copyright © 2015 John Wiley & Sons, Ltd.