R help - Apr 2005 - Residuals in gls

Dear R-helpers,

I am doing a multiple linear regression of an ozone time-series on time and 
other explanatory variables. I have been using the "lm" model but I am
recently
experimenting with "gls".

With the "lm" model I was able to look at the residuals by $res in the
"summary
(lm(...))" and then check with "acf" for autocorrelation in these
residuals
which had the same "length" with the original time-series. 

A similar action in "gls" would return only 5 values for residuals 
(Min,Q1,Med,Q3,Max). So I am estimating the residuals for the predicted 
time-series by subtracting $fitted from my original time-series. I would like to
ask if this a correct thing to do.

Thanks for reading,

Panos


-----------------------------------------------------

Dr Panos Hadjinicolaou

Centre for Atmospheric Science, Dept. of Chemistry
University of Cambridge
Lensfield Road
Cambridge CB2 1EW, UK

Work: +44 1223 763815
Home: +44 1223 327417

Fax:  +44 1223 763823

The `correct thing to do' even for lm is to use the generic accessor 
function residuals().   It may give a different answer even for lm 
(depending on na.action).

Similarly, use fitted() for the fitted values.

On Fri, 15 Apr 2005, Panos Hadjinicolaou wrote:
> I am doing a multiple linear regression of an ozone time-series on time and
> other explanatory variables. I have been using the "lm" model but
I am recently
> experimenting with "gls".
>
> With the "lm" model I was able to look at the residuals by $res
in the "summary
> (lm(...))" and then check with "acf" for autocorrelation in
these residuals
> which had the same "length" with the original time-series.
>
> A similar action in "gls" would return only 5 values for
residuals
> (Min,Q1,Med,Q3,Max). So I am estimating the residuals for the predicted
> time-series by subtracting $fitted from my original time-series. I would
like to
> ask if this a correct thing to do.
-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595