# What are the software limitations in all possible subsets selection in regression?

If I have a dependent variable and $N$ predictor variables and wanted my stats software to examine all the possible models, there would be $2^N$ possible resulting equations.

I am curious to find out what the limitations are with regard to $N$ for major/popular statistic software since as $N$ gets large there is a combinatorial explosion.

I’ve poked around the various web pages for packages but not been able to find this information. I would suspect a value of 10 – 20 for $N$?

If anyone knows (and has links) I would be grateful for this information.

Aside from R, Minitab, I can think of these packages SAS, SPPS, Stata, Matlab, Excel(?), any other packages I should consider?

I suspect 30–60 is about the best you’ll get. The standard approach is the leaps-and-bounds algorithm which doesn’t require fitting every possible model. In $R$, the leaps package is one implementation.
The documentation for the regsubsets function in the leaps package states that it will handle up to 50 variables without complaining. It can be “forced” to do more than 50 by setting the appropriate boolean flag.