This question is not as simple as might appear. As the data are time series one should be very concerned about the distribution of the residuals, Are the series stationary and if not are they integrated of the same order and cointegrated. The danger of spurious results is a very live issue. As an example the attached data file contains two series. The file cpi.csv contains data on the log of the Irish CPI for the period 1957 Quarter 1 to 2006 Quarter 2. It also contains data on a variable c which has been proposed as an indicator of the level of the CPI. If you complete the regression using lm() you will get an apparently good answer. In effect the variable c is cumulative rainfall in Armagh from 1857 Quarter 1 to 1906 Quarter 2. Despite the favourable regression results there is obviously no relationship between the variables.
My recommendation to Andre would be to study a good book on time-series analysis. One is not doing him a favour by recommending a procedure to him that may lead to spurious results when not applied properly. Best Regards John Frain On 31/03/07, Achim Zeileis <[EMAIL PROTECTED]> wrote:
On Sat, 31 Mar 2007, Andre Jung wrote: > Dear all, > > I have three timeseries Uts, Vts, Wts. The relation between the time > series can be expressed as > > Uts = x Vts + y Wts + residuals > > How would I feed this to lm() to evaluate the unknowns x and y? If the time series are aligned (and univariate) you can just do lm(Uts ~ Vts + Wts) If not, have a look at the "dynlm" and/or "dyn" packages. Z > Thanks, > andre > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
-- John C Frain Trinity College Dublin Dublin 2 Ireland www.tcd.ie/Economics/staff/frainj/home.html mailto:[EMAIL PROTECTED] mailto:[EMAIL PROTECTED]
______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
