R help - Oct 2010 - cv.lm() broken; cross validation vs. predict(interval="prediction")

<< repost because previous attempt was not plain text, sorry! >>

Hi Folks,
I have a pretty simple problem: after building a multivariate linear model,
I need to report my 95% confidence interval for predictions based on future
observations.

I know that one option is to use predict(interval="prediction") but
I'm curious about less parametric ways to get an estimate.

I tried doing K-fold cross validation using cv.lm() from the DAAG package,
but it currently only uses the first independent variable in the provided
linear model.  No warnings or anything.  There was a thread about this here
about 3 years ago but the person got no response.  Does anyone know of a
working alternative?

Thanks,
Dan

On 23.10.2010 00:17, Daniel Weitzenfeld wrote:
> <<  repost because previous attempt was not plain text,
sorry!>>
>
> Hi Folks,
> I have a pretty simple problem: after building a multivariate linear model,
> I need to report my 95% confidence interval for predictions based on future
> observations.
>
> I know that one option is to use predict(interval="prediction")
but
> I'm curious about less parametric ways to get an estimate.
>
> I tried doing K-fold cross validation using cv.lm() from the DAAG package,
> but it currently only uses the first independent variable in the provided
> linear model.  No warnings or anything.
Please report to the package maintainer.

Best,
Uwe Ligges

> There was a thread about this here
> about 3 years ago but the person got no response.  Does anyone know of a
> working alternative?
>
> Thanks,
> Dan
>
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