# StraussHard

0th

Percentile

##### The Strauss / Hard Core Point Process Model

Creates an instance of the Strauss/ hard core'' point process model which can then be fitted to point pattern data.

Keywords
spatial
##### Usage
StraussHard(r, hc)
##### Arguments
r
The interaction radius of the Strauss interaction
hc
The hard core distance
##### Details

A Strauss/hard core process with interaction radius $r$, hard core distance $h < r$, and parameters $\beta$ and $\gamma$, is a pairwise interaction point process in which

• distinct points are not allowed to come closer than a distance$h$apart
• each pair of points closer than$r$units apart contributes a factor$\gamma$to the probability density.

##### Value

• An object of class "interact" describing the interpoint interaction structure of the Strauss/hard core'' process with Strauss interaction radius $r$ and hard core distance hc.

##### eqn

$\log(\gamma)$

##### deqn

$$f(x_1,\ldots,x_n) = \alpha \beta^{n(x)} \gamma^{s(x)}$$

##### code

StraussHard()

##### References

Baddeley, A. and Turner, R. (2000) Practical maximum pseudolikelihood for spatial point patterns. Australian and New Zealand Journal of Statistics 42, 283--322.

Ripley, B.D. (1981) Spatial statistics. John Wiley and Sons.

Strauss, D.J. (1975) A model for clustering. Biometrika 63, 467--475.

mpl, pairwise.family, ppm.object

• StraussHard
##### Examples
library(spatstat)
StraussHard(r=1,hc=0.02)
# prints a sensible description of itself

data(cells)
mpl(cells, ~1, StraussHard(r=0.1, hc=0.05), rbord=0.1)
# fit the stationary Strauss/hard core  process to cells'

mpl(cells, ~ polynom(x,y,3), StraussHard(r=0.1, hc=0.05), rbord=0.1)
# fit a nonstationary Strauss/hard core process
# with log-cubic polynomial trend`
Documentation reproduced from package spatstat, version 1.4-3, License: GPL version 2 or newer

### Community examples

Looks like there are no examples yet.