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

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/gwr.whole.test.R

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

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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 [email protected] 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

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data(columbus)
col.bw <- gwr.sel(crime ~ income + housing, data=columbus,
  coords=cbind(columbus$x, columbus$y))
col.gauss <- gwr(crime ~ income + housing, 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 ~ income + housing, data=columbus,
  coords=cbind(columbus$x, columbus$y), gweight=gwr.bisquare)
col.bisq <- gwr(crime ~ income + housing, 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 May 29, 2017, 4:15 p.m.