rThomas {spatstat} | R Documentation |
Generate a random point pattern using the Thomas cluster process.
rThomas(lambda, sigma, mu, win = owin(c(0,1),c(0,1)))
lambda |
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 lambda
. 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"
).
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
X <- rThomas(10, 0.2, 5)