I think you will find that many readers of this list would rather try
to dissuade you from this misguided strategy. You are unlikely to get
to a sensible solution in using step-down procedures with this sort of
situation (large number of predictors with modest size of data).
--
David Winsemius
On Mar 12, 2009, at 1:59 PM, Paul Hermes wrote:
Hi,
Im using the lm() function where the formula is quite big (300
arguments) and the data is a frame of 3000 values.
This is running in a loop where in each step the formula is reduced
by one argument, and the lm command is called again (to check which
arguments are useful) .
This takes 1-2 minutes.
Is there a way to speed this up?
i checked the code of the lm function and its seems that its
preparing the data and then calls lm.Fit(). i thought about just
doing this praparing stuff first and only call lm.fit() 300 times.
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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