Large cokriging systems arise in many situations and are difficult to handle in practice. Simplifications such as simple kriging, strictly collocated and multicollocated cokriging are often used and models under which such simplifications are, in fact, equivalent to cokriging have recently received attention. In this paper, a two-dimensional second-order stationary random process with known mean is considered and the redundancy of certain components of the data at certain locations vis-a-vis the solution to the simple cokriging system is examined. Conditions for the simple cokriging weights of these components at these locations are set to zero. The conditions generalise the notion of the autokrigeability coefficient and can, in principle, ...
The sensitivity of the Kriging-based response surface (surrogate model) to co-variogram law characte...
Surrogate modeling plays an increasingly important role in different areas of aerospace engineering...
In this thesis, the Locally-Optimized Covariance (LOC) Kriging method is developed. This method repr...
Simple cokriging of components of a p-dimensional second-order stationary random process is consider...
Traditional approaches to predict a second-order stationary vector random field include simple and o...
This paper sets up the relations between simple cokriging and ordinary cokriging with one or several...
This work proposes to generalize the method of kriging when data are spatially sampled curves. A spa...
AbstractThis work proposes to generalize the method of kriging when data are spatially sampled curve...
International audienceOur goal in the present article to give an insight on some important questions...
The article describes the R-package constrainedKriging, a tool for spatial prediction problems that ...
Cokriging allows predicting coregionalized variables from sampling information, by considering their...
Kriging provides metamodels for deterministic and random simulation models. Actually, there are seve...
Kriging provides metamodels for deterministic and random simulation models. Actually, there are seve...
Abstract. A deficiency of kriging is the implicit assumption of second-order stationarity. We presen...
http://www.telecom-st-etienne.fr/Carraro/documents/articles/Ginsbourger_ENBIS07.pdfInternational aud...
The sensitivity of the Kriging-based response surface (surrogate model) to co-variogram law characte...
Surrogate modeling plays an increasingly important role in different areas of aerospace engineering...
In this thesis, the Locally-Optimized Covariance (LOC) Kriging method is developed. This method repr...
Simple cokriging of components of a p-dimensional second-order stationary random process is consider...
Traditional approaches to predict a second-order stationary vector random field include simple and o...
This paper sets up the relations between simple cokriging and ordinary cokriging with one or several...
This work proposes to generalize the method of kriging when data are spatially sampled curves. A spa...
AbstractThis work proposes to generalize the method of kriging when data are spatially sampled curve...
International audienceOur goal in the present article to give an insight on some important questions...
The article describes the R-package constrainedKriging, a tool for spatial prediction problems that ...
Cokriging allows predicting coregionalized variables from sampling information, by considering their...
Kriging provides metamodels for deterministic and random simulation models. Actually, there are seve...
Kriging provides metamodels for deterministic and random simulation models. Actually, there are seve...
Abstract. A deficiency of kriging is the implicit assumption of second-order stationarity. We presen...
http://www.telecom-st-etienne.fr/Carraro/documents/articles/Ginsbourger_ENBIS07.pdfInternational aud...
The sensitivity of the Kriging-based response surface (surrogate model) to co-variogram law characte...
Surrogate modeling plays an increasingly important role in different areas of aerospace engineering...
In this thesis, the Locally-Optimized Covariance (LOC) Kriging method is developed. This method repr...