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)
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