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?
Here's my R code for the simultaneous model fit (taking a phi estimate=0.6 from a previous step <ACF(glsfit)>):
glsAR1fit<-gls(y~x1+x2+x3+x4, na.action = na.omit, subset=12:54,
correlation = corARMA(0.6, p=1, q=0, fixed = FALSE))Thanks much,
Jeff
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Jeff Jorgensen
Center for Limnology University of Wisconsin Madison ph (608) 263-2304 680 North Park Street fx (608) 265-2340 Madison, Wisconsin 53706 http://limnology.wisc.edu
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