The first step should be to look at str(Daten90) str(Daten10)
and if that doesn't solve the problem, then consider a reproducible example, or at the very least posting the results of the above to this list. Sarah On Fri, Feb 22, 2019 at 7:38 AM <f-...@web.de> wrote: > > Dear all, > > I am currently working out a geographically weighted regression, in which 90% > of the data set the model should be calculated and for 10% of the values to > be predicted. For the prediction I use the function gwr.predict from the > package GWModel: > > Erg<-gwr.predict(formula=Ziel~ as.factor(Var1) + log(Var2, base = exp(1)) + > Var3, data = Daten90,predictdata = Daten10,bw = bwG, kernel = > "gaussian",adaptive = FALSE, p = 2, theta = 0, longlat = FALSE) > > I always get this error, although Daten10 and Daten90 have the same structure: > Error in gwr.predict(formula = Ziel~ as.factor(Var1) + log(Var2, base = > exp(1)) + Var3, : > All the independent variables should be included in the predictdata. > > Can you tell me what the problem with this code is? > Or is there any other way for a GWR and the prediction? > > Thank you, > Christoph > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-geo -- Sarah Goslee (she/her) http://www.numberwright.com _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
