Hi all,

I am fitting a simple model using lme() with random intercepts AR(1) errors
from the residuals. I have a question about how to get predicted values
from these models. My model call is the following:

# linear time trends with no covariates
model.a1 <- lme(log(child_mortality) ~ time , merged1, random= ~ 1
|country.x, correlation=corAR1(form = ~ time),
                 na.action=na.omit,method="ML")

Without corAR1() command one can trivially get predicted values using the
function predict(). Yet, using corAR1() the predict() function return
something else, possibly the AR(1) errors ( the returned values from using
predict() in this model is exactly the same for all units (country.x) in a
given year.).  I can provided more results with needed.

Any suggestions?

All the best,

Antonio.

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