# RPpoisson

From RandomFields v3.1.36
by Martin Schlather

##### Simulation of Random Fields

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

- Keywords
- spatial

##### 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

##### 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)
```

*Documentation reproduced from package RandomFields, version 3.1.36, License: GPL (>= 3)*

### Community examples

Looks like there are no examples yet.