Prepared with the support of the National Science Foundation grant no. CME-7919836The theory of intrinsic random functions of order k (IRF-K) and its use in optimal linear interpolation is presented using a simple deterministic formulation. Also outlined are the procedures for identification of generalized covariances corresponding to an IRF-K. Included is documentation, example and listing of a general purpose computer package for point and block kriging using IRF-K theory. The accessibility of such a tool should be welcomed by mining engineers, hydrologists and other geophysicists
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...
International audienceKriging is a special type of optimal linear prediction applied to random funct...
We consider the problem of spatial interpolation and outline the theory behind kriging and more spec...
This report deals with Kriging, a spatial interpolation-method that enables making predictions of th...
Indicator kriging (IK) is a spatial interpolation technique aimed at estimating the conditional cumu...
The presented bachelor thesis aims at interpolation method called kriging, which is based on regress...
International audienceThis paper presents a matrix formulation of factorial kriging, and its relatio...
Two techniques are commonly used to predict values of a random field u(t) from a vector of observati...
Two techniques are commonly used to predict values of a random field u(t) from a vector of observati...
Two techniques are commonly used to predict values of a random field u(t) from a vector of observati...
Two techniques are commonly used to predict values of a random field u(t) from a vector of observati...
The article describes the R-package constrainedKriging, a tool for spatial prediction problems that ...
Kriging is an interpolation technique whose optimality criteria are based on normality assumptions e...
In this survey we present various classical geostatistical prediction methods with a focus on interp...
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...
International audienceKriging is a special type of optimal linear prediction applied to random funct...
We consider the problem of spatial interpolation and outline the theory behind kriging and more spec...
This report deals with Kriging, a spatial interpolation-method that enables making predictions of th...
Indicator kriging (IK) is a spatial interpolation technique aimed at estimating the conditional cumu...
The presented bachelor thesis aims at interpolation method called kriging, which is based on regress...
International audienceThis paper presents a matrix formulation of factorial kriging, and its relatio...
Two techniques are commonly used to predict values of a random field u(t) from a vector of observati...
Two techniques are commonly used to predict values of a random field u(t) from a vector of observati...
Two techniques are commonly used to predict values of a random field u(t) from a vector of observati...
Two techniques are commonly used to predict values of a random field u(t) from a vector of observati...
The article describes the R-package constrainedKriging, a tool for spatial prediction problems that ...
Kriging is an interpolation technique whose optimality criteria are based on normality assumptions e...
In this survey we present various classical geostatistical prediction methods with a focus on interp...
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...
International audienceKriging is a special type of optimal linear prediction applied to random funct...