maxnndist
Compute Minimum or Maximum Nearest-Neighbour Distance
A faster way to compute the minimum or maximum nearest-neighbour distance in a point pattern.
Usage
minnndist(X, positive=FALSE, by=NULL)
maxnndist(X, positive=FALSE, by=NULL)Arguments
- X
A point pattern (object of class
"ppp").- positive
Logical. If
FALSE(the default), compute the usual nearest-neighbour distance. IfTRUE, ignore coincident points, so that the nearest neighbour distance for each point is greater than zero.- by
Optional. A factor, which separates
Xinto groups. The algorithm will compute the distance to the nearest point in each group.
Details
These functions find the minimum and maximum values
of nearest-neighbour distances in the point pattern X.
minnndist(X) and maxnndist(X) are
equivalent to, but faster than, min(nndist(X))
and max(nndist(X)) respectively.
The value is NA if npoints(X) < 2.
Value
A single numeric value (possibly NA).
If by is given, the result is a numeric matrix
giving the minimum or maximum nearest neighbour distance
between each subset of X.
See Also
Examples
# NOT RUN {
min(nndist(swedishpines))
minnndist(swedishpines)
max(nndist(swedishpines))
maxnndist(swedishpines)
minnndist(lansing, positive=TRUE)
if(interactive()) {
X <- rpoispp(1e6)
system.time(min(nndist(X)))
system.time(minnndist(X))
}
minnndist(amacrine, by=marks(amacrine))
maxnndist(amacrine, by=marks(amacrine))
# }