R: Simulation of Random Fields

RPpoisson {RandomFields} | R Documentation

## Simulation of Random Fields

### Description

Shot noise model, which is also called moving average model, trigger process, dilution random field, and by several other names.

### Usage

    RPpoisson(phi, intensity)

### Arguments

`phi` | the model, `RMmodel`, gives the shape function to be used
`intensity` | the intensity of the underlying stationary Poisson point process

### Author(s)

Martin Schlather, schlather@math.uni-mannheim.de http://ms.math.uni-mannheim.de/de/publications/software

### See Also

`RMmodel` RP, `RPcoins`

### Examples

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

    # example 1: Posson field based on disks with radius 1
    x <- seq(0,25, 0.02)
    model <- RMball()
    z <- RFsimulate(RPpoisson(model), x, intensity = 2)
    plot(z)
    par(mfcol=c(2,1))
    plot(z@data[,1:min(length(z@data), 1000)], type="l")
    hist(z@data[,1], breaks=0.5 + (-1 : max(z@data)))

    # example 2: Poisson field based on the normal density function
    # note that
    # (i) the normal density as unbounded support that has to be truncated
    # (ii) the intensity is high so that the CLT holds
    x <- seq(0, 10, 0.01)
    model <- RMtruncsupport(radius=5, RMgauss())
    z <- RFsimulate(RPpoisson(model), x, intensity = 100)
    plot(z)

[Package RandomFields version 3.1.50 Index]