RPspectral(phi, loggauss, sp_lines, sp_grid, prop_factor, sigma)RMmodel;
specifies the covariance model to be simulated. Default: 500.
grid=FALSE,
and $k\pi/$sp_lines
for $k$ in 1:sp_lines,
otherwise. This parameter is only considered
if the spectral measure, not the density is used.
Default: prop_factorsigma
is not positive thenRandomFields tries to find a good
choRPspectral returns an object of class
RMmodelergodic=FALSE,
the additive component are chosen proportional to their
variance. In total sp_lines are simulated. If
ergodic=TRUE, the components are simulated
separately and then added.
Default: FALSE.
}
1e-25.
}RFoptions(seed=0)
model <- RPspectral(RMmatern(nu=1))
y <- x <- seq(0,10,len=if (interactive()) 400 else 3)
z <- RFsimulate(model, x, y, n=2, grid=TRUE)
plot(z)
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