Description Implemented processes See Also Examples

Here, all classes of random fields are described that can be simulated.

Gaussian Random Fields | see Gaussian |

Max-stable Random Fields | see Maxstable |

Other Random Fields | Binary field |

chi2 field | |

composed Poisson (shot noise, random coin) | |

t field | |

RC, RR, RM, RF, R.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
x <- seq(0, 10, 0.1)
model <- RMexp()
## a Gaussian field with exponential covariance function
z <- RFsimulate(model, x)
plot(z)
## a binary field obtained as a thresholded Gaussian field
b <- RFsimulate(RPbernoulli(model), x)
plot(b)
sum( abs((z@data$variabl1 >=0 ) - b@data$variable1)) == 0 ## TRUE,
## i.e. RPbernoulli is indeed a thresholded Gaussian process
``` |

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