Nathan, It is a little challenging to keep up with your ability to ask this question here, on StackOverflow and again on r-devel. As I first saw it here, I'll answer here.
R is a dynamically-typed interpreted language with many bells and whistles, but also opaque memory management. My recommendation always is to "if in doubt and when working with large objects" to maybe just step aside and do something different outside of R. You mentioned logistic regression. And we did something similar at work: use Rcpp as well as bigmemory via external pointers (ie Rcpp::XPtr) so that *you* can allocate one chunk of memory *you* control, and keep at arm's length of R. Implementing a simple glm-alike wrapper over that to fit a logistic regression in then not so hard. We even did it in a multicore context to get extra parallelism still using only that one (large!!) chunk of memory. There are several articles in the Rcpp Gallery that should get you started. Hope this helps, Dirk -- http://dirk.eddelbuettel.com | @eddelbuettel | e...@debian.org _______________________________________________ Rcpp-devel mailing list Rcpp-devel@lists.r-forge.r-project.org https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
