# 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

```
# NOT RUN {
pp <- rGaussPoisson(30, 0.07, 0.5)
# }
```

*Documentation reproduced from package spatstat, version 1.64-1, License: GPL (>= 2)*