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 <adamsteve2000@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
> --
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