a Spatial*DataFrame, i.e. SpatialPointsDataFrame or SpatialPolygonsDataFrame as defined in package sp
bw
bandwidth used in the weighting function, probably calculated
by bw.gwr or bw.gwr.lcr; fixed (distance) or
adaptive bandwidth (number of nearest neighbours)
kernel
function chosen as follows:
gaussian: wgt = exp(-.5*(vdist/bw)^2);
exponential: wgt = exp(-vdist/bw);
bisquare: wgt = (1-(vdist/bw)^2)^2 if vdist < bw, wgt=0 otherwise;
tricube: wgt = (1-(vdist/bw)^3)^3 if vdist < bw, wgt=0 otherwise;
boxcar: wgt=1 if dist < bw, wgt=0 otherwise
adaptive
if TRUE calculate an adaptive kernel where the bandwidth (bw) corresponds to the number of nearest neighbours (i.e. adaptive distance); default is FALSE, where a fixed kernel is found (bandwidth is a fixed distance)
p
the power of the Minkowski distance, default is 2, i.e. the Euclidean distance
theta
an angle in radians to rotate the coordinate system, default is 0
longlat
if TRUE, great circle distances will be calculated
dMat
a pre-specified distance matrix, it can be calculated by the function gw.dist
Value
corr.mat
Local correlation matrix
VIF
Local Variance inflation factors (VIFs) matrix
local_CN
Local condition numbers
VDP
Local variance-decomposition proportions
SDF
a SpatialPointsDataFrame (may be gridded) or
SpatialPolygonsDataFrame object (see package “sp”) integrated with VIF, local_CN, VDP and corr.mat
Wheeler D, Tiefelsdorf M (2005) Multicollinearity and correlation among local
regression coefficients in geographically weighted regression. Journal of
Geographical Systems 7:161-187
Wheeler D (2007) Diagnostic tools and a remedial method for collinearity in
geographically weighted regression. Environment and Planning A 39:2464-2481