Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Dave Evens
> Sent: Thursday, June 16, 2011 11:33 AM
> To: r-help at r-project.org
> Subject: [R] prediction intervals
>
>
>
> Dear members,
>
> I'm fitting linear model using "lm" which has numerous auto-regressive
> terms as well as other explanatory variables. In order to calculate
> prediction intervals, i've used a for-loop as the auto-regressive
> parameters need to be updated each time so that a new forecast and
> corresponding prediction interval can be calculated.
>
> I'm fitting a number of these models which have different values for
> the response variable and possibly different explanatory variables. The
> response is temperature in fahrenheit (F), and the different models are
> for cities. So each city has its own fitted linear model for
> temperature. I'm assuming that they're independent models for the time
> being, I want to combine the results across all cities and have overall
> prediction intervals. Because I assuming that they're independent can I
> just add together the degrees of freedom from each model (i.e. total
> degrees of freedom=df1+df2+...) and the variance-covariance matrices
> (i.e. V=V1+V2+...) in order to calcalate the overall prediction
> intervals?
>
> Any help would be most appreciated.
>
> Regards,
> Dave
> [[alternative HTML version deleted]]
>
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