R: Bandwidth selection for generalised geographically weighted...
bw.ggwr
R Documentation
Bandwidth selection for generalised geographically weighted regression (GWR)
Description
A function for bandwidth selection to calibrate a generalised GWR model
Usage
bw.ggwr(formula, data, family ="poisson", approach="CV",
kernel="bisquare",adaptive=FALSE, p=2, theta=0, longlat=F,dMat)
Arguments
formula
Regression model formula of a formula object
data
a Spatial*DataFrame, i.e. SpatialPointsDataFrame or SpatialPolygonsDataFrame as defined in package sp
family
a description of the error distribution and link function to
be used in the model, which can be specified by “poisson” or “binomial”
approach
specified by CV for cross-validation approach or by AIC corrected (AICc) approach
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
providing 
.