[R] Etimating time to run an analysis?
gunter.berton at gene.com
Wed Nov 27 22:36:01 CET 2013
I would say that if the OP even contemplated this, it strongly
suggests that she needs to consult a local statistician for help.
On Wed, Nov 27, 2013 at 1:14 PM, Ben Bolker <bbolker at gmail.com> wrote:
> Erika Barthelmess <barthelmess <at> stlawu.edu> writes:
>> Hi everyone,
>> I'm new to this list and have searched R help prior for an answer
>> to this question, without luck. If I'm
>> posting in error, please forgive.
>> I'm thinking about using package MuMIn to do multimodel inference
>> with logistic regression. I have many
>> (25) possible predictors and am curious if there is a way to
>> estimate how long the dredge command might take
>> to run?
>> Any suggestions most welcome.
> 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.
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> and provide commented, minimal, self-contained, reproducible code.
Genentech Nonclinical Biostatistics
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