GSTAT - singular in meters not km

Edzer (and all),

I don't think that it's related to an unrealistic range. I've tried a 
lot of different realistic and non-realistic values and get singular 
results each time. If I divide the X and Y coordinates by 10, 100, 
1000 or 10000 I don't get singularity. Using Lat and Long works fine. 
Code is below and I included a link to a workspace with the "pol" data 
set at the bottom.

Zev

polA<-pol
coordinates(polA)<-~x+y
v<-variogram(pollutant~1, data=polA)
v.fit<-fit.variogram(v, vgm(0.0005, "Sph", 40000, 0.00001))
attributes(v.fit)$singular # TRUE

polB<-pol
polB$x<-polB$x/1000
polB$y<-polB$y/1000
coordinates(polB)<-~x+y
v<-variogram(pollutant~1, data=polB)
v.fit<-fit.variogram(v, vgm(0.0005, "Sph", 40, 0.00001))
attributes(v.fit)$singular #FALSE

polC<-pol
coordinates(polC)<-~longitude+latitude
v<-variogram(pollutant~1, data=polC)
v.fit<-fit.variogram(v, vgm(0.0005, "Sph", .4, 0.00001))
attributes(v.fit)$singular # FALSE

http://www.zevross.com/temp2/singular_or_not.RData

Edzer Pebesma wrote:

Hi Zev, it is hard to see what happens without seeing your data or R 
commands.

Is it possible that you passed an unrealistic value for the range 
parameter, as starting value for the variogram model argument of 
fit.variogram?
-- 
Edzer

Zev Ross wrote:

Hi All,

I'm fitting variograms in GSTAT with fit.variogram and I was 
surprised to find that all my fits were singular. I experimented 
with converting the data to unprojected data (decimal degrees) and 
with dividing my X and Y coordinates, which are in meters, by 1000 
(to get KM). In both cases the fitting procedure worked with no 
singularity. Based on the numbers of pairs the bins appeared to be 
about the same so it appears to be a matter of the coordinates 
themselves.

I'd prefer not to have to convert the coordinates back and forth 
between meters and KM, any suggestions?

Zev