This thread pointed out that the "plain vanilla" library for linear algebra outperformed the fancy ones for the original poster -- and he had mentioned this, but still got "you ought to ...." advice that was inappropriate and ignored his stated experience.
I've been surprised sometimes myself with performance results, and I'm now getting wary of making pronouncements. I always thought statistics was about using data sensibly to uncover truths. This is a case where we can actually get the data pretty easily. Perhaps the R posting guide needs an addition to say "When discussing performance, you really should present some data and not just speculation." Ultimately we need good performance benchmarks. They are difficult to set up properly and tedious to run. Maybe a good subject for a Google Summer of Code project for next year or some undergraduate projects. JN ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
