Hi Bob,
Thanks for the suggestion.
I figured out a way to force the polygon plot order, by referencing one
of the attributes of the imported shapefile. The polygons I used were
6th field HUCs and I was able to use this attribute to order plotting:
shape<-readShapePoly(shapefile)#shapefile has
Hi Jeff,
This is what I did.
HistBreaks<-quantile(datafileDf$nhunters,probs=c(0.1,0.2,
0.4,0.6,0.8,0.9,1.0),na.rm=TRUE)
np<-findInterval(datafileDf$nhunters, histBreaks, all.inside=TRUE)
colorsToUse<-colorSchemeV5
plot.polylist(datafilePolys, col=colorsToUse[np], forcefill=FALSE)
plot.polylist(d
Hello,
I've imported a shapefile of polygons (R v2.5.1 winxp, maptools v0.6-13)
and I'm trying to assign colors to polygons in plot.polylist(). Is
there a way to force the order in which polygons are plotted get the
correct color associations to the corresponding polygons?
Best regards,
Jeff
On Wed, 18 Jul 2007, Ryan Rosario wrote:
> I understand that the sum.w field is the sum of the weights associated with
> a particular observation/location.
This is apparently a follow-up to a question on 15 July about robust GWR.
GWR is seriously affected by multicollinearity anyway (see Wheeler
I'm trying to specify a model where the fixed effects are
dep ~ group + group:indep
and the error variance and spatial autocorrelation vary by group. I've
tried lme but AFAICT it only supports heteroscedasticity and
autocorrelation within groups. Any pointers?
THK
--
Timothy H. Keitt, Universi
Edzer Pebesma wrote:
> David, you may also notice that the map produced does not have a cell
> centre or cell 'crossing' at (0,0). Of course you'd assume enough
> cleverness that this would be enforced automatically, but too bad. Try
>
> v <- variogram(Ni ~ 1, jura.pred, cutoff=1.8, width=0.18,
David, you may also notice that the map produced does not have a cell
centre or cell 'crossing' at (0,0). Of course you'd assume enough
cleverness that this would be enforced automatically, but too bad. Try
v <- variogram(Ni ~ 1, jura.pred, cutoff=1.8, width=0.18, map=T)
(making sure that the
I understand that the sum.w field is the sum of the weights associated with
a particular observation/location.
But what is this sum taken over? Is there a way to access the individual
weights before they are summed?
Basically, I need a single weight for each observation (not a sum), so that
I can
I've found a quite puzzling behaviour in gstat's variogram method, with
the map=T argument. I believe the result should be a symmetric map
because all the semivariances are squared differences. This is indeed
the case if I try an example from the Meuse set:
> library(gstat)
> data(meuse)
> coordin
