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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