rHardcore
Perfect Simulation of the Hardcore Process
Generate a random pattern of points, a simulated realisation of the Hardcore process, using a perfect simulation algorithm.
Usage
rHardcore(beta, R = 0, W = owin())Arguments
- beta
- intensity parameter (a positive number).
- R
- hard core distance (a non-negative number).
- W
- window (object of class
"owin") in which to generate the random pattern. Currently this must be a rectangular window.
Details
This function generates a realisation of the
Hardcore point process in the window W
using a
The Hardcore process is a model for strong spatial inhibition.
Two points of the process are forbidden to lie closer than
R units apart.
The Hardcore process is the special case of the Strauss process
(see rStrauss)
with interaction parameter $\gamma$ equal to zero.
The simulation algorithm used to generate the point pattern
is rmh, whose output
is only approximately correct).
There is a tiny chance that the algorithm will run out of space before it has terminated. If this occurs, an error message will be generated.
Value
- A point pattern (object of class
"ppp").
References
Berthelsen, K.K. and Moller, J. (2002) A primer on perfect simulation for spatial point processes. Bulletin of the Brazilian Mathematical Society 33, 351-367.
Berthelsen, K.K. and Moller, J. (2003) Likelihood and non-parametric Bayesian MCMC inference for spatial point processes based on perfect simulation and path sampling. Scandinavian Journal of Statistics 30, 549-564.
Moller, J. and Waagepetersen, R. (2003). Statistical Inference and Simulation for Spatial Point Processes. Chapman and Hall/CRC.
See Also
Examples
X <- rHardcore(0.05,1.5,square(141.4))
Z <- rHardcore(100,0.05)