RandomFields (version 3.1.16)

Hyperplane: Hyperplane method

Description

The Hyperplane method is a simulation method for stationary, isotropic random fields with exponential covariance function. It is based on a tessellation of the space by hyperplanes. Each cell takes a spatially constant value of an i.i.d. random variable. The superposition of several such random fields yields approximatively a Gaussian random field.

Usage

RPhyperplane(phi, boxcox, superpos, maxlines, mar_distr, mar_param ,additive)

Arguments

phi

object of class RMmodel; specifies the covariance function to be simulated; only exponential covariance functions and scale mixtures of it are allowed.

boxcox

the one or two parameters of the box cox transformation. If not given, the globally defined parameters are used. see RFboxcox for Details.

superpos

integer. number of superposed hyperplane tessellations. Default: 300.

maxlines

integer. Maximum number of allowed lines. Default: 1000.

mar_distr

integer. code for the marginal distribution used in the simulation:

0

uniform distribution

1

Frechet distribution with form parameter mar_param

2

Bernoulli distribution (Binomial with $n=1$) with argument mar_param

This argument should not be changed yet. Default: 0.

mar_param

Argument used for the marginal distribution. The argument should not be changed yet. Default: NA.

additive

logical. If TRUE independent realisations are added, else the maximum is taken.

Default: TRUE.

Value

RPhyperplane returns an object of class RMmodel

References

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

See Also

Gaussian, RP.

Examples

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

model <- RPhyperplane(RMexp(s=2), superpos=1)
x <- seq(0, 3, 0.04)
z <- RFsimulate(x=x, x, model=model, n=1)
plot(z)