Re: [R] Predictkion interval using regression coefficients

From: Joshua Wiley <jwiley.psych_at_gmail.com>
Date: Tue, 12 Apr 2011 11:59:20 -0700

Hi Zeda,

The short answer to your question is no. All you have are the parameter estimates with no information on variability which you would need to create a prediction interval. Given the great ease of fitting models in R, I would offer to refit the model for my boss, and then (with the model in R), just use its handy predict() function to calculate whatever predictions with any desired confidence with ease (and graph them). See ?predict and for basic linear models ?lm

Cheers,

Josh

On Tue, Apr 12, 2011 at 10:54 AM, Zd Gibbs <zd.gibbs_at_yahoo.com> wrote:
> I was given a list of parameter estimates from my boss. She wants to predict the
> dependent variable "fsshen" beyond jan 2011, the last observation, through
> December 2011, giving the prediction intervals (90%). I don't know if I have the
> complete information to do this. So my question(s) is can R determine a
> prediction interval from this data with just these parameter estimates. And if
> so, how?
>
> Thanks all who can help.
>
> Zeda.
>
> Here are the parameter estimates:
> Jan dummy 108.422
> Feb dummy 107.619
> Mrc dummy 80.515
> Apr dummy 95.307
> May dummy 92.340
> Jun dummy 99.866
> Jul dummy 83.276
> Aug dummy 78.763
> Sep dummy 83.717
> Oct dummy 103.963
> Nov dummy 63.060
> Dec dummy 27.147
> coeff. on "SalesLag11" 0.423
>        [[alternative HTML version deleted]]
>
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>

-- 
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/

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