Dear R-sig-Geo members,
a semivariogram for spatial soil data, calculated by the gls (nlme library)
function gives the following estimates:
> lmm.dap2b <- gls(Dap.sa ~ 1 + ID.sitio, Pd2006mm,
> correlation=corGaus(form=~(easting.m+northing.m)|ID.sitio, nugget=TRUE,
> metric="euclidean"), na.action=na.omit, method="REML")
> Variogram(lmm.dap2b)
variog dist n.pairs
1 0.3059585 2.828427 122
2 0.4040062 4.269282 125
3 0.5744688 18.110770 123
4 0.5266091 20.000000 125
....
whereas the variogram function of the gstat library gives, for similar
distances (although different number of sample pairs), very different gamma
values:
> variogram(Dap.sa ~ 1, locations = ~ easting.m + northing.m, data=Pd2006mm,
> cutoff=80)
np dist gamma dir.hor dir.ver id
1 219 3.225693 0.005578128 0 0 var1
2 20 6.478671 0.004254656 0 0 var1
3 3 13.513045 0.009896324 0 0 var1
4 307 19.201322 0.009708390 0 0 var1
.....
Can anyone explain what is happening?
Thanks for any advice,
Guido Lorenz
Can anyone explain
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