ggwr.Rd
The function implements generalised geographically weighted regression approach to exploring spatial nonstationarity for given global bandwidth and chosen weighting scheme.
ggwr(formula, data = list(), coords, bandwidth, gweight = gwr.Gauss, adapt = NULL, fit.points, family = gaussian, longlat = NULL, type = c("working", "deviance", "pearson", "response"))
formula  regression model formula as in 

data  model data frame as in 
coords  matrix of coordinates of points representing the spatial positions of the observations 
bandwidth  bandwidth used in the weighting function, possibly
calculated by 
gweight  geographical weighting function, at present

adapt  either NULL (default) or a proportion between 0 and 1 of observations to include in weighting scheme (knearest neighbours) 
fit.points  an object containing the coordinates of fit points; often an object from package sp; if missing, the coordinates given through the data argument object, or the coords argument are used 
family  a description of the error distribution and link function to
be used in the model, see 
longlat  TRUE if point coordinates are longitudelatitude decimal degrees, in which case distances are measured in kilometers; if x is a SpatialPoints object, the value is taken from the object itself 
type  the type of residuals which should be returned. The alternatives are: "working" (default), "pearson", "deviance" and "response" 
A list of class “gwr”:
a SpatialPointsDataFrame (may be gridded) or SpatialPolygonsDataFrame object (see package "sp") with fit.points, weights, GWR coefficient estimates, dispersion if a "quasi"family is used, and the residuals of type "type" in its "data" slot.
Leung et al. L matrix, here set to NA
GLM global regression on the same model formula.
the bandwidth used.
the function call used.
Fotheringham, A.S., Brunsdon, C., and Charlton, M.E., 2002, Geographically Weighted Regression, Chichester: Wiley; http://gwr.nuim.ie/
The use of GWR on GLM is only at the initial proof of concept stage, nothing should be treated as an accepted method at this stage.
if (require(rgdal)) { xx < readOGR(system.file("shapes/sids.shp", package="spData")[1]) bw < 144.4813#> Error: <text>:5:0: unexpected end of input #> 3: bw < 144.4813 #> 4: #> ^bw < ggwr.sel(SID74 ~ I(NWBIR74/BIR74) + offset(log(BIR74)), data=xx, family=poisson(), longlat=TRUE)#> Error in is(data, "Spatial"): object 'xx' not foundnc < ggwr(SID74 ~ I(NWBIR74/BIR74) + offset(log(BIR74)), data=xx, family=poisson(), longlat=TRUE, bandwidth=bw)#> Error in is(data, "SpatialPolygonsDataFrame"): object 'xx' not foundnc#> Error in eval(expr, envir, enclos): object 'nc' not foundnc < ggwr(SID74 ~ I(NWBIR74/10000) + offset(log(BIR74)), data=xx, family=poisson(), longlat=TRUE, bandwidth=bw)#> Error in is(data, "SpatialPolygonsDataFrame"): object 'xx' not foundnc#> Error in eval(expr, envir, enclos): object 'nc' not foundnc < ggwr(SID74 ~ I(NWBIR74/10000) + offset(log(BIR74)), data=xx, family=quasipoisson(), longlat=TRUE, bandwidth=bw)#> Error in is(data, "SpatialPolygonsDataFrame"): object 'xx' not foundnc#> Error in eval(expr, envir, enclos): object 'nc' not found}#> Error: <text>:1:1: unexpected '}' #> 1: } #> ^