On May 22, 2011, at 12:35 PM, Dave Evens wrote:
Dear all,
I'm fitting a linear model with numerous lag terms of the response
variable [i.e. y(t-1), y(t-2),y(t-3)...,] and other explanatory
variables [x(1), x(2), x(3),....]- which go into my design matrix X.
I'm fitting the linear model: lm(Y ~ X, ...).
I would like to use the predict.lm function however the future
predictions of Y are dependent upon previous predictions of Y [i.e.
the response lag terms]. Does anyone know how I would go about using
predict.lm to make future forecasts of Y? Or, does this have to be
writting as a for loop that recursively updates the lag terms for
each future prediction of y(i)? The data is a time series and the
model is only calculated once in order to make the future predictions.
There is a 'forecast' package.
--
David Winsemius, MD
West Hartford, CT
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