## S3 method for class 'lpp':
nnfun(X, ...)"lpp").function in the Rlanguage, with arguments x,y and optional
arguments seg,tp.
It also belongs to the class "linfun" which has methods
for plot, print etc.X on a linear network L
tells us which point of X is closest to
any given location.
If X is a point pattern on a linear network L,
the nearest neighbour function of X
is the mathematical function $f$ defined for any
location $s$ on the network by f(s) = i, where
X[i] is the closest point of X to the location s
measured by the shortest path. In other words the value of f(s)
is the identifier or serial number of the closest point of X.
The command nnfun.lpp is a method for the generic command
nnfun
for the class "lpp" of point patterns on a linear network. If X is a point pattern on a linear network,
f <- nnfun(X) returns a function
in the Rlanguage, with arguments x,y, ..., that represents the
nearest neighbour function of X. Evaluating the function f
in the form v <- f(x,y), where x and y
are any numeric vectors of equal length containing coordinates of
spatial locations, yields the values of the distance function at these
locations. More efficiently f can take the arguments
x, y, seg, tp where seg and tp are the local
coordinates on the network.
The result of f <- nnfun(X) also belongs to the class
"linfun".
It can be printed and plotted immediately as shown in the Examples.
It can be converted to a pixel image
using as.linim.
linfun,
methods.linfun. To compute the distance to the nearest neighbour, see
distfun.lpp.
data(letterR)
X <- runiflpp(3, simplenet)
f <- nnfun(X)
f
plot(f)Run the code above in your browser using DataLab