| DiggleGratton {spatstat.model} | R Documentation |
Diggle-Gratton model
Description
Creates an instance of the Diggle-Gratton pairwise interaction point process model, which can then be fitted to point pattern data.
Usage
DiggleGratton(delta=NA, rho)
Arguments
delta |
lower threshold |
rho |
upper threshold |
Details
Diggle and Gratton (1984, pages 208-210)
introduced the pairwise interaction point
process with pair potential h(t) of the form
h(t) = \left( \frac{t-\delta}{\rho-\delta} \right)^\kappa
\quad\quad \mbox{ if } \delta \le t \le \rho
with h(t) = 0 for t < \delta
and h(t) = 1 for t > \rho.
Here \delta, \rho and \kappa
are parameters.
Note that we use the symbol \kappa
where Diggle and Gratton (1984) and Diggle, Gates and Stibbard (1987)
use \beta, since in spatstat we reserve the symbol
\beta for an intensity parameter.
The parameters must all be nonnegative,
and must satisfy \delta \le \rho.
The potential is inhibitory, i.e.\ this model is only appropriate for
regular point patterns. The strength of inhibition increases with
\kappa. For \kappa=0 the model is
a hard core process with hard core radius \delta.
For \kappa=\infty the model is a hard core
process with hard core radius \rho.
The irregular parameters
\delta, \rho must be given in the call to
DiggleGratton, while the
regular parameter \kappa will be estimated.
If the lower threshold delta is missing or NA,
it will be estimated from the data when ppm is called.
The estimated value of delta is the minimum nearest neighbour distance
multiplied by n/(n+1), where n is the
number of data points.
Value
An object of class "interact"
describing the interpoint interaction
structure of a point process.
Author(s)
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner rolfturner@posteo.net and Ege Rubak rubak@math.aau.dk
References
Diggle, P.J., Gates, D.J. and Stibbard, A. (1987) A nonparametric estimator for pairwise-interaction point processes. Biometrika 74, 763 – 770.
Diggle, P.J. and Gratton, R.J. (1984) Monte Carlo methods of inference for implicit statistical models. Journal of the Royal Statistical Society, series B 46, 193 – 212.
See Also
Examples
ppm(cells ~1, DiggleGratton(0.05, 0.1))