`rGaussPoisson(kappa, r, p2, win = owin(c(0,1),c(0,1)))`

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`

.- 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`

.

`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`

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

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