RPpoisson: Simulation of Poisson Random Fields

In RandomFields: Simulation and Analysis 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

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)

RandomFields documentation built on Jan. 19, 2022, 1:06 a.m.