# rStraussHard

##### Perfect Simulation of the Strauss-Hardcore Process

Generate a random pattern of points, a simulated realisation of the Strauss-Hardcore process, using a perfect simulation algorithm.

##### Usage

`rStraussHard(beta, gamma = 1, R = 0, H = 0, W = owin(), expand=TRUE)`

##### Arguments

- beta
- intensity parameter (a positive number).
- gamma
- interaction parameter (a number between 0 and 1, inclusive).
- R
- interaction radius (a non-negative number).
- H
- hard core distance (a non-negative number smaller than
`R`

). - W
- window (object of class
`"owin"`

) in which to generate the random pattern. Currently this must be a rectangular window. - expand
- Logical. If
`FALSE`

, simulation is performed in the window`W`

, which must be rectangular. If`TRUE`

(the default), simulation is performed on a larger window, and the result is clipped to the original wind

##### Details

This function generates a realisation of the
Strauss-Hardcore point process in the window `W`

using a

The Strauss-Hardcore process is described in `StraussHard`

.

The simulation algorithm used to generate the point pattern
is `rmh`

, whose output
is only approximately correct).

A limitation of the perfect simulation algorithm
is that the interaction parameter
$\gamma$ must be less than or equal to $1$.
To simulate a Strauss-hardcore process with
$\gamma > 1$, use `rmh`

.

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.
}
`"ppp"`

).*Bulletin of the Brazilian Mathematical Society* 33, 351-367.

Berthelsen, K.K. and *Scandinavian Journal of Statistics* 30, 549-564.

*Statistical Inference and Simulation for Spatial Point Processes.*
Chapman and Hall/CRC.
}
[object Object],[object Object]
`rmh`

,
`rStrauss`

,
`StraussHard`

.

*Documentation reproduced from package spatstat, version 1.37-0, License: GPL (>= 2)*