nnfun.lpp

Nearest Neighbour Map on Linear Network

Compute the nearest neighbour function of a point pattern on a linear network.

Usage

## S3 method for class 'lpp':
nnfun(X, ...)

Details

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 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.

See Also

linfun, methods.linfun.

To compute the distance to the nearest neighbour, see distfun.lpp.

Aliases

• nnfun.lpp

Examples

data(letterR)
   X <- runiflpp(3, simplenet)
   f <- nnfun(X)
   f
   plot(f)