[R] correcting for autocorrelation in models with panel data?

[Doran, Harold]

In the nlme package you can find the gls() function to account for
autocorrelation over time using corAR1. Syntax might look something like
this:

fm1 <- gls(response ~ IV, long, correlation=corAR1(form=~1|ID),
method='ML')

You can also use weights() for heteroscedasticity.

-Harold

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of David Hugh-Jones
Sent: Thursday, February 10, 2005 12:15 PM
To: r-help at stat.math.ethz.ch
Subject: [R] correcting for autocorrelation in models with panel data?

Hi 

I have some panel data for the 50 US states over about 25 years, and I
would like to test a simple model via OLS, using this data. I know how
to run OLS in R, and I think I can see how to  create Panel Corrected
Standard Errors using

http://jackman.stanford.edu/classes/350C/pcse.r

What I can't figure out is how to correct for autocorrelation over time.
I have found a lot of R stuff on time series models but they all seem
focused on predicting a single variable from its previous values.
Can anyone explain to me how to detect and get round autocorrelation?
Is there a package for panel data that I have missed?

I appreciate that this is probably just as much about my ignorance of
econometrics as about R itself!

Cheers
David

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