On Wed, Jun 27, 2012 at 4:36 AM, Christof Kluß <ckl...@email.uni-kiel.de> wrote: > > for example the same model with intercept R² = 0.6, without intercept R² > = 0.9 and higher. In my definition of R², R² has to be equal or less > without intercept > > I do not know what R shows, but in the summary of the model without > intercept it does not show the R² of the regression line. > > When I run a regression I like to have the R² of the regression line and > not something else. ;) >
If we use a baseline with no intercept in the R^2 definition then adding the intercept will always improve the R^2 or at least not make the R^2 worse. The following r.squared.0 function defines such an R^2. It will agree with the R^2 produced by R when used with models having no intercept but will give a different R^2 value for models with an intercept. r.squared.0 <- function(fm) c(1 / (1 + crossprod(resid(fm)) / crossprod(fitted(fm)))) fm1 <- lm(demand ~ Time, BOD) fm0 <- lm(demand ~ Time-1, BOD) r.squared.0(fm0) r.squared.0(fm1) # adding intercept increases r.squared.0 # for comparison # summary(fm0) uses same defn as r.squared.0 # but summary(fm1) does not summary(fm0)$r.squared # does agree with ours summary(fm1)$r.squared # does not agree with ours -- Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com ______________________________________________ R-help@r-project.org 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.
