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Research Article
Intrinsic Kriging and prior information
Article first published online: 23 MAR 2005
DOI: 10.1002/asmb.536
Copyright © 2005 John Wiley & Sons, Ltd.
Issue
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Applied Stochastic Models in Business and Industry
Special Issue: Statistical Learning
Volume 21, Issue 2, pages 215–226, March/April 2005
Additional Information
How to Cite
Vazquez, E., Walter, E. and Fleury, G. (2005), Intrinsic Kriging and prior information. Appl. Stochastic Models Bus. Ind., 21: 215–226. doi: 10.1002/asmb.536
Publication History
- Issue published online: 23 MAR 2005
- Article first published online: 23 MAR 2005
- Abstract
- References
- Cited By
Keywords:
- black-box models;
- grey-box models;
- Kriging;
- regularization;
- semi-parametric models
Abstract
Kriging, one of the oldest prediction methods based on reproducing kernels, can be used to build black-box models in engineering. In practice, however, it is often necessary to take into account prior information to obtain satisfactory results. First, the kernel (the covariance) can be used to specify properties of the prediction such as its regularity or the correlation distance. Moreover, intrinsic Kriging (viewed as a semi- parametric formulation of Kriging) can be used with an additional set of factors to take into account a specific type of prior information. We show that it is thus very easy to transform a black-box model into a grey-box one. The prediction error is orthogonal in some sense to the prior information that has been incorporated. An application in flow measurement illustrates the interest of the method. Copyright © 2005 John Wiley & Sons, Ltd.