Cross-validation score for a specified bandwidth for basic GWR

Share:

Description

This function finds the cross-validation score for a specified bandwidth for basic GWR. It can be used to construct the bandwidth function across all possible bandwidths and compared to that found automatically.

Usage

1
2
gwr.cv(bw, X, Y, kernel="bisquare",adaptive=FALSE, dp.locat, p=2, theta=0, 
       longlat=F,dMat, verbose=T)

Arguments

bw

bandwidth used in the weighting function;fixed (distance) or adaptive bandwidth(number of nearest neighbours)

X

a numeric matrix of the independent data with an extra column of “ones” for the 1st column

Y

a column vector of the dependent data

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)

dp.locat

a two-column numeric array of observation coordinates

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

verbose

if TRUE (default), reports the progress of search for bandwidth

Value

CV.score

cross-validation score

Author(s)

Binbin Lu binbinlu@whu.edu.cn

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.