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
lm and time series: simple question
2 messages · mwh@indiana.edu, Brian Ripley
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) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595