Timeline for What programming language for statistical inference?
Current License: CC BY-SA 3.0
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| Jun 12, 2016 at 6:52 | history | edited | Nick Cox | CC BY-SA 3.0 |
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| Nov 22, 2010 at 22:25 | comment | added | chl |
I'll second @Matt and @mbq's comment about R performance, but I'd like to add that R is pretty good actually for (N)LMEs. I can remember a talk from Doug Bates at the DSC 2009 conference where he showed how the lme4 package easily handles a lot of random effects (as encountered e.g., in educational assessment). My own (but limited) experience (SAS NLMIXED vs. R lme4) confirms that point: R is by no way slower than SAS when it comes to apply complex IRT models, and it handles large data genetic sets as well (thanks to clever C implementation).
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| Nov 22, 2010 at 16:00 | comment | added | Matt Parker | +1 because this answer is useful, but I think your points about R's support, speed, and ability to handle large data are out of date or becoming so fairly quickly. | |
| Nov 22, 2010 at 9:30 | comment | added | user88 | Well, R support are places like here, which are often more effective that a paid support. For Googling, there is rseek.org, works very nice. 99% of R-is-slow cases can be solved with some thinking; there are also packages to deal with huge data (it is not straightforward in SAS neither). R is a programming language, SAS is an extended SQL. | |
| S Nov 22, 2010 at 5:44 | history | answered | MichaelSnot | CC BY-SA 2.5 | |
| S Nov 22, 2010 at 5:44 | history | made wiki | Post Made Community Wiki |