The random coin method (or dilution method) is simulation method for
stationary Gaussian random fields. It is based on the following procedure:
For a stationary Poisson point process on $R^d$
consider the random field
$$Y(y) = \sum_{x\in X} f(y-x)$$
for a function $f$. The covariance of $Y$ is
proportional to the convolution
$$C(h) = \int f(x)f(x+h) dx $$
If the intensity of the Poisson point process increases, the
random field $Y$ is approaches a Gaussian random field
with covariance function $C$.
Usage
RPcoins(phi, shape, boxcox, intensity, method)
RPaverage(phi, shape, boxcox, intensity, method)
Arguments
phi
object of class RMmodel;
specifies the covariance function of the Poisson process;
either phi or shape must be given.
shape
object of class RMmodel;
specifies the function which is attached to the Poisson points;
note that this is not the covariance function of the simulated
random field.
boxcox
the one or two parameters of the box cox transformation.
If not given, the globally defined parameters are used.
see RFboxcox for Details.
intensity
positive number, intensity of the underlying Poisson
point process.
method
integer.
Default is the value 0 which addresses the current standard
procedure. There might be further methods implemented mainly for
internal purposes.