GWR.R
In spgwr: Geographically Weighted Regression

## ---- echo=FALSE, results="hide"----------------------------------------------
load(system.file("backstore/nyGWR.RData", package="spgwr"))

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library(spgwr)

## ---- eval=FALSE--------------------------------------------------------------
#  NY8 <- as(st_read(system.file("shapes/NY8_utm18.shp", package="spData")), "Spatial")

## ---- eval=FALSE--------------------------------------------------------------
#  bwG <- gwr.sel(Z~PEXPOSURE+PCTAGE65P+PCTOWNHOME, data=NY8, gweight=gwr.Gauss, verbose=FALSE)
#  gwrG <- gwr(Z~PEXPOSURE+PCTAGE65P+PCTOWNHOME, data=NY8, bandwidth=bwG, gweight=gwr.Gauss, hatmatrix=TRUE)

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gwrG

## ---- eval=FALSE--------------------------------------------------------------
#  gbwG <- ggwr.sel(Cases~PEXPOSURE+PCTAGE65P+PCTOWNHOME+offset(log(POP8)), data=NY8, family="poisson", gweight=gwr.Gauss, verbose=FALSE)
#  ggwrG <- ggwr(Cases~PEXPOSURE+PCTAGE65P+PCTOWNHOME+offset(log(POP8)), data=NY8, family="poisson", bandwidth=gbwG, gweight=gwr.Gauss)

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ggwrG

## ---- fig.caption="GWR local coefficient estimates for the exposure to TCE site covariate"----
spplot(ggwrG$SDF, "PEXPOSURE", col.regions=grey.colors(7, 0.95, 0.55, 2.2), cuts=6)

## ---- fig.caption="plots of GWR local coefficient estimates showing the effects of GWR collinearity forcing"----
pairs(as(ggwrG$SDF, "data.frame")[,2:5])