spatstat (version 1.42-0)

distfun.lpp: Distance Map on Linear Network

Description

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

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.

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.

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.

See Also

linfun, methods.linfun.

To identify which point is the nearest neighbour, see nnfun.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))