kriging {RGeostats}  R Documentation 
Kriging procedure
kriging(dbin, dbout, model = model.input(), neigh = neigh.input(), uc = c("1"), mean = NA, flag.linked = FALSE, calcul = "point", ndisc = NA, mat.CL = NA, nostat = NA, cov.extract = NA, drift.extract = NA, flag.est = TRUE, flag.std = TRUE, flag.varz=FALSE, rank.colcok = NA, flag.grad = FALSE, var.save=NA, ball.radius = 1,radix = "Kriging",modify.target = db.locmod())
dbin 
The 
dbout 
The 
model 
The 
neigh 
The 
uc 
The drift description. Use command 
mean 
Array containing the mean of each variable, used in the case of Simple (Co)Kriging 
flag.linked 
When TRUE, the variables are sharing the same mean (or more generally the same drift). Otherwise, the variables have separate means (drifts). 
calcul 
Kriging option:

ndisc 
Array giving the number of discretisation points in each direction of the space. If the dimension of the argument 'ndisc' does not match the space dimension, this vector is set to 1 in each direction, leading to a point estimation. 
mat.CL 
Array giving the expression of the output variables (nvarout) as a function of the input variables (nvarin). The number of input variables must correspond to the number of variables for which the argument 'model' is defined. The dimension of 'mat.CL' is nvarout (nrow) x nvarin (ncol). 
nostat 
List of nonstationary parameters.
For details see 
cov.extract 
List of the ranks of the basic covariance structures to be extracted. Setting it to 0 filters out all the basic covariance structures. 
drift.extract 
List of the ranks of the drift basic components to be extracted. Setting if to 0 filters out all the drift basic components. 
flag.est 
When TRUE, the estimations are required 
flag.std 
When TRUE, the standard deviation of estimations are required 
flag.varz 
When TRUE, the variances of the estimators are required 
rank.colcok 
Array of ranks for the colocated variables, in the case of a
colocation option. For more information, check 
flag.grad 
When TRUE and if gradient components are defined in the input

var.save 
Array of the ranks of the variables for which the results are stored. If left undefined, the results of all variables are stored. 
ball.radius 
Radius of the ball used for Gradient integration 
radix 
Radix of the name given to the variables storing the results in the target Db. 
modify.target 
Decides whether or not the newly created variables will have their
locator defined or not. For more information, see 
The target Db where the following variables have been added:
the estimation variable (if flag.est=TRUE)
the standard deviation variable (if flag.std=TRUE)
These variables are multiplied for each one of the data variables.