R help - Jun 2005 - lm and time series: simple question

Hello:

This question is partly about R and partly out of my ignorance about time
series.

I want to regress one time series on another, taking into account the
autocorrelation (in an AR1 model) within each series.  I am interested in how
the standard error changes when the acf is taken into account.

I've made both of my datasets into ts objects and used the basic lm function
(with na.action=NULL) to no effect (i.e. the resulting standard error is the
same as if they were not times series).  I've also looked at binding the two
series together with ts.union or ts.intersect, but then I am left with a single
object, and don't understand how to regress one of the components of this
onto
the other.


Any help on this subject would be appreciated.


cheers,
Matt

On Thu, 16 Jun 2005 mwh at indiana.edu wrote:
> This question is partly about R and partly out of my ignorance about 
> time series.
>
> I want to regress one time series on another, taking into account the
> autocorrelation (in an AR1 model) within each series.  I am interested in
how
> the standard error changes when the acf is taken into account.
This does not happen with least-squares fitting as done by lm. You can use 
arima or gls (in package nlme).  Note that both assume a model for the 
residuals, not for the series themselves.

You could also make a joint model of the two time series.  That is 
probably not what you want.
> I've made both of my datasets into ts objects and used the basic lm 
> function (with na.action=NULL) to no effect (i.e. the resulting standard 
> error is the same as if they were not times series).  I've also looked 
> at binding the two series together with ts.union or ts.intersect, but 
> then I am left with a single object, and don't understand how to
regress
> one of the components of this onto the other.
-- 
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)
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