# distfun.lpp

0th

Percentile

##### Distance Map on Linear Network

Compute the distance function of a point pattern on a linear network.

Keywords
spatial, math
##### Usage
## S3 method for class 'lpp':
distfun(X, ...)
##### Arguments
X
A point pattern on a linear network (object of class "lpp").
...
Extra arguments are ignored.
##### Details

On a linear network $L$, the geodesic distance function of a set of points $A$ in $L$ is the mathematical function $f$ such that, for any location $s$ on $L$, the function value f(s) is the shortest-path distance from $s$ to $A$.

The command distfun.lpp is a method for the generic command distfun for the class "lpp" of point patterns on a linear network.

If X is a point pattern on a linear network, f <- distfun(X) returns a function in the Rlanguage that represents the distance 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 function f obtained from f <- distfun(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.

##### Value

• A function 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 identify which point is the nearest neighbour, see nnfun.lpp.

• distfun.lpp
##### Examples
data(letterR)
X <- runiflpp(3, simplenet)
f <- distfun(X)
f
plot(f)

# using a distfun as a covariate in a point process model:
Y <- runiflpp(4, simplenet)
fit <- lppm(Y, ~D, covariates=list(D=f))
Documentation reproduced from package spatstat, version 1.42-2, License: GPL (>= 2)

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