R help - Mar 2011 - Degrees of freedom for lm in logLik and AIC

I have a question about the computation of the degrees of freedom in a linear
model:

x <- runif(20); y <- runif(20)
f <- lm(y ~ x)
logLik(f)
'log Lik.' -1.968056 (df=3)

The 3 is coming from f$rank + 1.  Shouldn't it be f$rank?  This affects
AIC(f).
Thanks
Frank

-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
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On Mar 28, 2011, at 05:36 , Frank Harrell wrote:
> I have a question about the computation of the degrees of freedom in a
linear
> model:
> 
> x <- runif(20); y <- runif(20)
> f <- lm(y ~ x)
> logLik(f)
> 'log Lik.' -1.968056 (df=3)
> 
> The 3 is coming from f$rank + 1.  Shouldn't it be f$rank?  This affects
> AIC(f).
I count three parameters in a simple linear regression: alpha, beta, sigma.

From a generic-likelihood point of view, I don't see how you can omit the
last one.

-pd

-- 
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com