LMZ.F3GWR.test: Global tests of geographical weighted regressions

In spgwr: Geographically Weighted Regression

Global tests of geographical weighted regressions

Description

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).

Usage

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)

Arguments

go, x, object	a gwr object returned by gwr()
...	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

Details

The papers in the references give the background for the analyses of variance presented.

Value

BFC99.GWR.test, BFC02.gwr.test, LMZ.F1GWR.test and LMZ.F2GWR.test return "htest" objects, LMZ.F3GWR.test a matrix of test results.

Author(s)

Roger Bivand [e-mail] and Danlin Yu

References

Fotheringham, A.S., Brunsdon, C., and Charlton, M.E., 2002, Geographically Weighted Regression, Chichester: Wiley; http://gwr.nuim.ie/

See Also

gwr

Examples

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)

spgwr documentation built on July 9, 2023, 6:04 p.m.