Open source is a development method for software that harnesses the power of distributed peer review and transparency of process. The promise of open source is better quality, higher reliability, more flexibility, lower cost, and an end to predatory vendor lock-in.
I frequently see complaints about the performance of R. Most recently, this started with a series of blog posts from Radford Neal and followed by responses from many others including Christian Robert, Dirk Eddelbuettel, and Andrew Gelman.
I'm not going to reiterate what has already been said more ably by others who are far more intelligent and qualified, but I did want to make a few casual observations about why I feel that some of these authors are approaching this from the wrong direction:
All that said, I was really disappointed in Andrew Gelman's blog post most of all, and he seems more interested in the fact that he thinks that "the culture of R has some problems" rather than focusing on its strengths. Professor Gelman doesn't think that CRAN is "all that"; he could take or leave most of it if someone would only reprogram the main functions more elegantly in another language.
There are plenty of things about R that can be improved; performance is one of them. Is every package on CRAN perfectly crafted, or even useful? No. But CRAN is a remarkable gift to the world, full of things from the basic and useful to the esoteric and innovative models for data analysis. We should not overlook what we have in R: a language designed for data analysis that is constantly evolving through a huge, global effort of experts. And while it's hard to think about something after the fact, I suspect that what is happening in R couldn't have happened in another language. Community matters.