
Dear list users,

I have a problem with interpreting the results of corclasses. I used corARMA to correct for timeseries and themodel improved significantly. But I don't understand what the model actually did. To correct for timeseries i would think you need to give some input about time. My timevariable is TransJaarCod, which is the transactionyear. Do I have to include that in the random effect like in the last inputexample? Does the model calculate timeseries for GebID in the first example?


model3.8.fit<-lme(y~x1+LnBankt500+LnVoorzDagel500+LnBanIndDistr500+Perceelkwaliteit+PGebouwd+Bouwjaar_cat4+TransJaarCod, random = ~1|GebID , data, method = "REML")
model4.2.fit <- update(model3.8.fit, correlation = corARMA(p=1, q=1))



model3.9.fit<-lme(y~x1+LnBankt500+LnVoorzDagel500+LnBanIndDistr500+Perceelkwaliteit+PGebouwd+Bouwjaar_cat4+TransJaarCod, random = ~1|GebID/TransJaarCod , data, method = "REML")
model4.3.fit <- update(model3.9.fit, correlation = corARMA(p=1, q=1))


And how does the model account for spatial autocorrelation? For spatial corClasses you don't need the x and y coordinates. How does this work?



Sorry if these are stupid questions.

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