View source: R/gwr.whole.test.R
LMZ.F3GWR.test | R Documentation |
Four related test statistics for comparing OLS and GWR models based on bapers by Brunsdon, Fotheringham and Charlton (1999) and Leung et al (2000), and a development from the GWR book (2002).
LMZ.F3GWR.test(go) LMZ.F2GWR.test(x) LMZ.F1GWR.test(x) BFC99.gwr.test(x) BFC02.gwr.test(x, approx=FALSE) ## S3 method for class 'gwr' anova(object, ..., approx=FALSE)
go, x, object |
a |
... |
arguments passed through (unused) |
approx |
default FALSE, if TRUE, use only (n - tr(S)) instead of (n - 2*tr(S) - tr(S'S)) as the GWR degrees of freedom |
The papers in the references give the background for the analyses of variance presented.
BFC99.GWR.test, BFC02.gwr.test, LMZ.F1GWR.test and LMZ.F2GWR.test return "htest" objects, LMZ.F3GWR.test a matrix of test results.
Roger Bivand Roger.Bivand@nhh.no and Danlin Yu
Fotheringham, A.S., Brunsdon, C., and Charlton, M.E., 2002, Geographically Weighted Regression, Chichester: Wiley; http://gwr.nuim.ie/
gwr
data(columbus, package="spData") col.bw <- gwr.sel(CRIME ~ INC + HOVAL, data=columbus, coords=cbind(columbus$X, columbus$Y)) col.gauss <- gwr(CRIME ~ INC + HOVAL, data=columbus, coords=cbind(columbus$X, columbus$Y), bandwidth=col.bw, hatmatrix=TRUE) BFC99.gwr.test(col.gauss) BFC02.gwr.test(col.gauss) BFC02.gwr.test(col.gauss, approx=TRUE) anova(col.gauss) anova(col.gauss, approx=TRUE) ## Not run: col.d <- gwr.sel(CRIME ~ INC + HOVAL, data=columbus, coords=cbind(columbus$X, columbus$Y), gweight=gwr.bisquare) col.bisq <- gwr(CRIME ~ INC + HOVAL, data=columbus, coords=cbind(columbus$X, columbus$Y), bandwidth=col.d, gweight=gwr.bisquare, hatmatrix=TRUE) BFC99.gwr.test(col.bisq) ## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.