EconPapers    
Economics at your fingertips  
 

A note on the choice and the estimation of Kriging models for the analysis of deterministic computer experiments

David Ginsbourger, Delphine Dupuy, Anca Badea, Laurent Carraro and Olivier Roustant

Applied Stochastic Models in Business and Industry, 2009, vol. 25, issue 2, 115-131

Abstract: Our goal in the present article to give an insight on some important questions to be asked when choosing a Kriging model for the analysis of numerical experiments. We are especially concerned about the cases where the size of the design of experiments is relatively small to the algebraic dimension of the inputs. We first fix the notations and recall some basic properties of Kriging. Then we expose two experimental studies on subjects that are often skipped in the field of computer simulation analysis: the lack of reliability of likelihood maximization with few data and the consequences of a trend misspecification. We finally propose an example from a porous media application, with the introduction of an original Kriging method in which a non‐linear additive model is used as an external trend. Copyright © 2009 John Wiley & Sons, Ltd.

Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://doi.org/10.1002/asmb.741

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:25:y:2009:i:2:p:115-131

Access Statistics for this article

More articles in Applied Stochastic Models in Business and Industry from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-20
Handle: RePEc:wly:apsmbi:v:25:y:2009:i:2:p:115-131