| rThomas {spatstat} | R Documentation |
Generate a random point pattern, a realisation of the Thomas cluster process.
rThomas(kappa, sigma, mu, win = owin(c(0,1),c(0,1)))
kappa |
Intensity of the Poisson process of cluster centres. A single positive number. |
sigma |
Standard deviation of displacement of a point from its cluster centre. |
mu |
Expected number of points per cluster. |
win |
Window in which to simulate the pattern.
An object of class "owin"
or something acceptable to as.owin.
|
This algorithm generates a realisation of the Thomas process, a special case of the Neyman-Scott process.
The algorithm
generates a uniform Poisson point process of ``parent'' points
with intensity kappa. Then each parent point is
replaced by a random cluster of points, the number of points
per cluster being Poisson (mu) distributed, and their
positions being isotropic Gaussian displacements from the
cluster parent location.
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.
Adrian Baddeley adrian@maths.uwa.edu.au http://www.maths.uwa.edu.au/~adrian/ and Rolf Turner rolf@math.unb.ca http://www.math.unb.ca/~rolf
rpoispp,
rMatClust,
rNeymanScott
X <- rThomas(10, 0.2, 5)