

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

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