Gradient of a field
RMderiv
is a multivariate covariance model which
models a field and its gradient.
For an isotropic covariance model varphi, the covariance C given by
RMderiv equals
C_{11}(x,y) = \varphi(\| x - y\|)
C_{j1}(x,y) = -C_{1j}(x,y) = \partial \varphi(\|x - y\|) / \partial x
C_{i,j}(x,y) = \partial^2 \varphi(\|x - y\|) / \partial x \partial y
for i,j = 2,…, d where d is the dimension of the field.
RMderiv(phi, which, var, scale, Aniso, proj)
phi |
a univariate stationary covariance model (in 2 or 3 dimensions). |
which |
vector of integers. If not given all components are returned; otherwise the selected components are returned. |
var,scale,Aniso,proj |
optional arguments; same meaning for any
|
Martin Schlather, schlather@math.uni-mannheim.de, https://www.wim.uni-mannheim.de/schlather/
Matheron
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again model <- RMderiv(RMgauss(), scale=4) plot(model, dim=2) x.seq <- y.seq <- seq(-10, 10, 0.4) simulated <- RFsimulate(model=model, x=x.seq, y=y.seq) plot(simulated)
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