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

David Ginsbourger (1) , Delphine Dupuy (1) , Anca Badea (1) , Laurent Carraro (1) , Olivier Roustant (1)

1 3MI-ENSMSE - Département Méthodes et Modèles Mathématiques pour l'Industrie

Our goal in the present work is 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 small relatively 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 external trend.

Mots clés: Metamodeling; Kriging; Maximum Likelihood; Deter- minisitic Drift; Additive Models

Domaines: Modélisation et simulation; Autres [stat.ML]

David Ginsbourger, Delphine Dupuy, Anca Badea, Laurent Carraro, Olivier Roustant. A note on the choice and the estimation of Kriging models for the analysis of deterministic computer experiments. 2008. ⟨hal-00270173⟩