Simulation of Random Fields
Shot noise model, which is also called moving average model, trigger process, dilution random field, and by several other names.
- the model,
RMmodel, gives the shape function to be used
- the intensity of the underlying stationary Poisson point process
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)
Looks like there are no examples yet.