| kNearestNeighbors {spatialprobit} | R Documentation |
Build Spatial Weight Matrix from k Nearest Neighbors
Description
Build a spatial weight matrix W using the k nearest neighbors of (x, y) coordinates
Usage
kNearestNeighbors(x, y, k = 6)
Arguments
x |
x coordinate |
y |
y coordinate |
k |
number of nearest neighbors |
Details
Determine the k nearest neighbors for a set of n points represented by (x, y)
coordinates and build a spatial weight matrix W (n \times n).
W will be a sparse matrix representation and row-standardised.
This method is a convenience method for quickly creating a spatial weights matrix based
on planar coordinates. More ways to create W are
available in knearneigh of package spdep.
Value
The method returns a sparse spatial weight matrix W with dimension
(n \times n) and k non-zero entries per row
which represent the k nearest neighbors.
Author(s)
Stefan Wilhelm <wilhelm@financial.com>
See Also
nb2listw and knearneigh
for computation of neighbors lists, spatial weights and standardisation.
Examples
require(Matrix)
# build spatial weight matrix W from random (x,y) coordinates
W <- kNearestNeighbors(x=rnorm(100), y=rnorm(100), k=6)
image(W, main="spatial weight matrix W")