[R] R squared for lm prediction

[Jeff Newmiller]

Or use the summary function on the lm object.

"Thomas Stewart" <tgstewart at gmail.com> wrote:

>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 at 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.
>>
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>>
>
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>
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