spatstat.core (version 2.1-2)

# rGaussPoisson: Simulate Gauss-Poisson Process

## Description

Generate a random point pattern, a simulated realisation of the Gauss-Poisson Process.

## Usage

```rGaussPoisson(kappa, r, p2, win = owin(c(0,1),c(0,1)),
…, nsim=1, drop=TRUE)```

## Arguments

kappa

Intensity of the Poisson process of cluster centres. A single positive number, a function, or a pixel image.

r

Diameter of each cluster that consists of exactly 2 points.

p2

Probability that a cluster contains exactly 2 points.

win

Window in which to simulate the pattern. An object of class `"owin"` or something acceptable to `as.owin`.

Ignored.

nsim

Number of simulated realisations to be generated.

drop

Logical. If `nsim=1` and `drop=TRUE` (the default), the result will be a point pattern, rather than a list containing a point pattern.

## Value

A point pattern (an object of class `"ppp"`) if `nsim=1`, or a list of point patterns if `nsim > 1`.

Additionally, some intermediate results of the simulation are returned as attributes of the point pattern. See `rNeymanScott`.

## Details

This algorithm generates a realisation of the Gauss-Poisson point process inside the window `win`. The process is constructed by first generating a Poisson point process of parent points with intensity `kappa`. Then each parent point is either retained (with probability `1 - p2`) or replaced by a pair of points at a fixed distance `r` apart (with probability `p2`). In the case of clusters of 2 points, the line joining the two points has uniform random orientation.

In this implementation, parent points are not restricted to lie in the window; the parent process is effectively the uniform Poisson process on the infinite plane.

`rpoispp`, `rThomas`, `rMatClust`, `rNeymanScott`
```# NOT RUN {