# gwr.cv: Cross-validation score for a specified bandwidth for basic... In GWmodel: Geographically-Weighted Models

## 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 [email protected]

GWmodel documentation built on May 29, 2017, 11:46 a.m.