edge.Trans(X, Y = X, W = X$window,
exact = FALSE, paired = FALSE,
...,
trim = spatstat.options("maxedgewt"),
dx=NULL, dy=NULL)"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 edX and Y. See Details.For 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. The arguments dx and dy can be provided as
an alternative to X and Y.
If paired=TRUE then dx,dy should be vectors of equal length
such that the vector difference of the $i$th pair is
c(dx[i], dy[i]). If paired=FALSE then
dx,dy should be matrices of the same dimensions,
such that the vector difference between X[i] and Y[j] is
c(dx[i,j], dy[i,j]). The argument W is needed.
edge.Ripley,
setcov,
Kestv <- edge.Trans(cells)Run the code above in your browser using DataCamp Workspace