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GWmodel (version 2.4-1)

bw.gwr.lcr: Bandwidth selection for locally compensated ridge GWR (GWR-LCR)

Description

A function for automatic bandwidth selection for gwr.lcr via a cross-validation approach only

Usage

bw.gwr.lcr(formula, data, kernel="bisquare",
        lambda=0,lambda.adjust=FALSE,cn.thresh=NA,
        adaptive=FALSE, p=2, theta=0, longlat=F,dMat)

Value

Returns the adaptive or fixed distance bandwidth

Arguments

formula

Regression model formula of a formula object

data

a Spatial*DataFrame, i.e. SpatialPointsDataFrame or SpatialPolygonsDataFrame as defined in package sp, or a sf object defined in package sf

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

p

the power of the Minkowski distance, default is 2, i.e. the Euclidean distance

lambda

option for a globally-defined (constant) ridge parameter. Default is lambda=0, which gives a basic GWR fit

lambda.adjust

a locally-varying ridge parameter. Default FALSE, refers to: (i) a basic GWR without a local ridge adjustment (i.e. lambda=0, everywhere); or (ii) a penalised GWR with a global ridge adjustment (i.e. lambda is user-specified as some constant, other than 0 everywhere); if TRUE, use cn.tresh to set the maximum condition number. For locations with a condition number (for its local design matrix), above this user-specified threshold, a local ridge parameter is found

cn.thresh

maximum value for condition number, commonly set between 20 and 30

adaptive

if TRUE calculate an adaptive kernel where the bandwidth 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)

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

Author

Binbin Lu binbinlu@whu.edu.cn

References

Gollini I, Lu B, Charlton M, Brunsdon C, Harris P (2015) GWmodel: an R Package for exploring Spatial Heterogeneity using Geographically Weighted Models. Journal of Statistical Software 63(17): 1-50