Jeff Jorgensen <[EMAIL PROTECTED]> writes: > Hi R-sters, > > Just wondering what I might be doing wrong. I'm trying to fit a > multiple linear regression model, and being ever mindful about the > possibilities of autocorrelation in the errors (it's a time series), > the errors appear to follow an AR1 process (ar(ts(glsfit$residuals)) > selected order 1). So, when I go back and try to do the simultaneous > regression and error fit with gls, the acf and pacf plots of residuals > from the old model (glsfit) and those plots of the new model > (glsAR1fit, below) look exactly the same (a significant > autocorrelation at lag of 1). > > Any ideas out there as to what I may be doing wrong? Is there an > error in my code?
This is one of the dangers of accessing model fit structures directly: There is more than one way to define residuals for correlated data. Try looking at help(residuals.gls). (It's been a while, but as far as I remember, you can plot the Variogram of the raw residuals and overlay the theoretical Variogram of the fitted model, so raw residuals are useful too. Also, standardized residuals are not uniquely defined since matrix square roots aren't.) -- O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
