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
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