rDiggleGratton(beta, delta, rho, kappa=1, W = owin(), expand=TRUE, nsim=1)
delta
)."owin"
) in which to
generate the random pattern. Currently this must be a rectangular
window.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
windW
using a 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)
use $\beta$, since in
The parameters must all be nonnegative, and must satisfy $\delta \le \rho$.
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.
}
nsim = 1
, a point pattern (object of class "ppp"
).
If nsim > 1
, a list of point patterns.
Berthelsen, K.K. and
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.
rmh
,
DiggleGratton
,
rStrauss
,
rHardcore
.