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Etimating time to run an analysis?

Erika Barthelmess <barthelmess <at> stlawu.edu> writes:
This is likely to be a bad idea.  With 25 predictors you have 2^25 =
33 million candidate models (you can think of an array of models, each
predictor is either present or absent in each model -- that makes this
a set of 25-digit binary strings ...).  (If this doesn't make sense,
convince yourself by writing out the number of possible models for a
1-parameter (2), 2-parameter (4), and 3-parameter (8) model, and do
the extrapolation.) So pick a model of intermediate complexity, run
it, see how long it takes, and multiply that by 33 million ...  (if
each model takes about one second to fit, the analysis will take
about a year to run).

  You might want to look into penalized regression approaches
(e.g. see the glmnet package), which are a much more efficient
approach to this type of problem.