# rThomas

0th

Percentile

##### Simulate Thomas Process

Generate a random point pattern using the Thomas cluster process.

Keywords
spatial
##### Usage
rThomas(lambda, sigma, mu, win = owin(c(0,1),c(0,1)))
##### Arguments
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.
##### Details

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.

##### Value

• The simulated point pattern (an object of class "ppp").

rpoispp, rNeymanScott
X <- rThomas(10, 0.2, 5)