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 toas.owin
. - ...
- Ignored.
- nsim
- Number of simulated realisations to be generated.
- drop
- Logical. If
nsim=1
anddrop=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"
) ifnsim=1
, or a list of point patterns ifnsim > 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)