I'm not sure I understand what you want, but here is a guess. Let y be the hold out response values. Let y.hat be the model predictions for the corresponding ys.
The key is to remember that R^2 = cor( y , y.hat )^2. So, cor( cbind(y,y.hat))[1,2]^2 should give you a measure you want. -tgs On Mon, Oct 4, 2010 at 10:06 PM, Brima <adamsteve2...@yahoo.com> wrote: > > Hi all, > > I have used a hold out sample to predict a model but now I want to compute > an R squared value for the prediction. Any help is appreciated. > > Best regards > -- > View this message in context: > http://r.789695.n4.nabble.com/R-squared-for-lm-prediction-tp2955328p2955328.html > Sent from the R help mailing list archive at Nabble.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. > [[alternative HTML version deleted]] ______________________________________________ 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.
