Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
| From | tlv101@gmx.net |
| To | statalist@hsphsun2.harvard.edu |
| Subject | st: Testing to compare goodness of fit |
| Date | Tue, 04 Oct 2011 22:35:22 +0200 |
Hello, I have two univariate time series models, both explaining variable Y, one with variable X and one with variable Z as the explanatory variable (plus a constant). Now, both models yield an R-squared that is rather close to each other. Can I really say that model X is better than model Z just by comparing these R-squareds (since with 5 observation more or less, things might look different)? Or can I test whether these r-squareds are statistically different from each other? Any other idea to evaluate goodness of fit in that case, except for comparing RMSE? Or is in this case comparing (f-testing) the coefficients of X and Z helpful? -- NEU: FreePhone - 0ct/min Handyspartarif mit Geld-zurück-Garantie! Jetzt informieren: http://www.gmx.net/de/go/freephone * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/