edge.Trans(X, Y = X, W = X$window,
exact = FALSE, paired = FALSE,
trim = spatstat.options("maxedgewt"))"ppp").TRUE, a slow algorithm will be used
to compute the exact value. If FALSE, a fast algorithm
will be used to compute the approximate value.X and Y
are paired. If TRUE, compute
the edge correction for corresponding points
X[i], Y[i] for all i.
If FALSE, compute the edFor a pair of points $x$ and $y$ in a window $W$, the translation edge correction weight is $$e(u, r) = \frac{\mbox{area}(W)}{\mbox{area}(W \cap (W + y - x))}$$ where $W + y - x$ is the result of shifting the window $W$ by the vector $y - x$. The denominator is the area of the overlap between this shifted window and the original window.
The function edge.Trans computes this edge correction weight.
If paired=TRUE, then X and Y should contain the
same number of points. The result is a vector containing the
edge correction weights e(X[i], Y[i]) for each i.
If paired=FALSE,
then the result is a matrix whose i,j entry gives the
edge correction weight e(X[i], Y[j]).
Computation is exact if the window is a rectangle. Otherwise,
exact=TRUE, the edge
correction weights are computed exactly usingoverlap.owin, which can be quite slow.exact=FALSE(the default),
the weights are computed rapidly by evaluating the
set covariance functionsetcovusing the Fast Fourier Transform.trim,
it is set to trim.edge.Ripley,
setcov,
Kestv <- edge.Trans(cells)Run the code above in your browser using DataCamp Workspace