Dear All, Consider yield as attribute and easting and northing in meters as spatial coordinates. I used gls function of nlme package because of spatial dependency of the residual. I tried to remove large-scale trend by using the easting and northing as covariates of yield.
model.vc<-gls(yield~easting+northing,method="ML"). Being a spatial data, we are most interested in carrying out variogram modelling of the spatial structure on the small-scale component i.e. the residual and equally fit the spatial correlation structure on the residual as well. Do I need to obtain the residual from the model.vc above i.e resid<-residuals(model.vc) and fit the other models as follow model.sph<-gls(resid~1,corr=CorSpher(form=~easting+northing, nugget=T)) or model.sph<-update(model.vc,corSpher(form=~easting+northing,nugget=T)) Please which one is correct. Thank you. Moshood [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo