R: Random coin method

Coins {RandomFields} | R Documentation

## Random coin method

### Description

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) = ∑_{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.

### Value

`RPcoins` returns an object of class `RMmodel`

### Author(s)

Martin Schlather, schlather@math.uni-mannheim.de

### References

- Lantuejoul, C. (2002) Geostatistical Simulation: Models and Algorithms. Springer.

### See Also

Gaussian, RP, `RPhyperplane`, `RPspectral`, `RPtbm`.

### Examples

    RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
    ##                   RFoptions(seed=NA) to make them all random again

[Package RandomFields version 3.1.50 Index]