# 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)),
..., 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.

##### 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

- 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`

.

##### See Also

##### Examples

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

*Documentation reproduced from package spatstat, version 1.41-1, License: GPL (>= 2)*