| nnfun.lpp | R Documentation |
Compute the nearest neighbour function of a point pattern on a linear network.
## S3 method for class 'lpp'
nnfun(X, ..., k=1, value=c("index", "mark"))
X |
A point pattern on a linear network
(object of class |
k |
Integer. The algorithm finds the |
value |
String (partially matched) specifying whether to return the
index of the neighbour ( |
... |
Other arguments are ignored. |
The (geodesic) nearest neighbour function of a
point pattern 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 R language, 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 a vector of identifiers or serial numbers of
the data points closest to these spatial 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.
A function in the R language, with arguments x,y and optional
arguments seg,tp.
It also belongs to the class "linfun" which has methods
for plot, print etc.
linfun,
methods.linfun.
To compute the distance to the nearest neighbour, see
distfun.lpp.
X <- runiflpp(3, simplenet)
f <- nnfun(X)
f
plot(f)
plot(nnfun(chicago, value="m"))
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