# rGaussPoisson

##### Simulate Gauss-Poisson Process

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)))`

##### 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`

.

##### 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.

##### Value

- The simulated point pattern (an object of class
`"ppp"`

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

`rNeymanScott`

.

##### See Also

##### Examples

`pp <- rGaussPoisson(30, 0.07, 0.5)`

*Documentation reproduced from package spatstat, version 1.20-2, License: GPL (>= 2)*