edge.Ripley(X, r, W = Window(X), method = "C", maxweight = 100)
rmax.Ripley(W)"ppp").
"interpreted" or "C".
This is needed only for debugging purposes.
edge.Ripley
computes Ripley's (1977) isotropic edge correction
weight, which is used in estimating the $K$ function and in many
other contexts. The function rmax.Ripley computes the maximum value of
distance $r$ for which the isotropic edge correction
estimate of $K(r)$ is valid.
For a single point $x$ in a window $W$,
and a distance $r > 0$, the isotropic edge correction weight
is
$$
e(u, r) = \frac{2\pi r}{\mbox{length}(c(u,r) \cap W)}
$$
where $c(u,r)$ is the circle of radius $r$ centred at the
point $u$. The denominator is the length of the overlap between
this circle and the window $W$.
The function edge.Ripley computes this edge correction weight
for each point in the point pattern X and for each
corresponding distance value in the vector or matrix r.
If r is a vector, with one entry for each point in
X, then the result is a vector containing the
edge correction weights e(X[i], r[i]) for each i.
If r is a matrix, with one row for each point in X,
then the result is a matrix whose i,j entry gives the
edge correction weight e(X[i], r[i,j]).
For example edge.Ripley(X, pairdist(X)) computes all the
edge corrections required for the $K$-function.
If any value of the edge correction weight exceeds maxwt,
it is set to maxwt.
The function rmax.Ripley computes the smallest distance $r$
such that it is possible to draw a circle of radius $r$, centred
at a point of W, such that the circle does not intersect the
interior of W.
edge.Trans,
rmax.Trans,
Kest
v <- edge.Ripley(cells, pairdist(cells))
rmax.Ripley(Window(cells))
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