| RFcovmatrix {RandomFields} | R Documentation |
RFcovmatrix returns the covariance matrix for a set of points;
RFcovmatrix(model, x, y = NULL, z = NULL, T = NULL, grid, params,
distances, dim,...)
model,params |
object of class |
x |
vector of x coordinates, or object of class |
y,z |
optional vectors of y (z) coordinates, which should not be given if |
T |
optional vector of time coordinates, |
grid |
logical; the function finds itself the correct value in nearly all cases, so that usually |
distances,dim |
another alternative for the argument |
... |
for advanced use: further options and control arguments for the simulation that are passed to and processed by |
RFcovmatrix returns a covariance matrix. Here, a matrix of coordinates (x) or a vector or a matrix of distances
is expected.
RFcovmatrix also allows for variogram models. Then the negative of the
variogram matrix is returned.
RFcovmatrix returns a covariance matrix.
Martin Schlather, schlather@math.uni-mannheim.de, http://ms.math.uni-mannheim.de
RMmodel,
RFsimulate,
RFfit,
RFfctn,
RFcalc,
RFcov,
RFpseudovariogram,
RFvariogram.
################################################## # Example: get covariance matrix C(x_i,x_j) # at given locations x_i, i=1,...,n # # here for an isotropic stationary covariance model # yields a 4 times 4 covariance matrix of the form # C(0) C(5) C(3) C(2.5) # C(5) C(0) C(4) C(2.5) # C(3) C(4) C(0) C(2.5) # C(2.5) C(2.5) C(2.5) C(0) model <- RMexp() # the covariance function C(x,y)=C(r) of this model # depends only on the distance r between x and y RFcovmatrix(model=model, distances=c(5,3,2.5,4,2.5,2.5), dim=4)