bw.gwss.average: Bandwidth selection for GW summary averages

In GWmodel: Geographically-Weighted Models

Bandwidth selection for GW summary averages

Description

A function for automatic bandwidth selections to calculate GW summary averages, including means and medians, via a cross-validation approach.

Usage

bw.gwss.average(data, summary.locat, vars, kernel = "bisquare", adaptive = FALSE, 
               p = 2, theta = 0, longlat = F, dMat)

Arguments

data	a Spatial*DataFrame, i.e. SpatialPointsDataFrame or SpatialPolygonsDataFrame as defined in package sp
summary.locat	a Spatial*DataFrame object for providing summary locations, i.e. SpatialPointsDataFrame or SpatialPolygonsDataFrame as defined in package sp
vars	a vector of variable names to be summarized
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

Returns the adaptive or fixed distance bandwidths (in a two-column matrix) for calculating the averages of each variable.

Author(s)

Binbin Lu [e-mail]

GWmodel documentation built on July 9, 2023, 5:52 p.m.