Darren’s blog was very helpful as I got started learning about bayesian inference, so it’s very neat to see Rainier appear there. (Also, he’s been a wonderful beta tester and now contributor. Thanks!)https://twitter.com/darrenjw/status/1002685644777377799 …
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That's pretty harsh on Stan, though mostly on syntax? We're working on a proposal for Stan 3 which seeks primarily to address the code modularity issues (and will add some syntactic niceties like type and block inference); curious if that scratches the itch, or what's missing...
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I don't know precisely what
@darrenjw had in mind. I would agree that Stan doesn't feel like modern, full-fledged PL (compared to say, Elm, which is also tiny and special purpose but I would be happy to call "elegant"). But I wouldn't have assumed that was even a goal? -
2/3 Stan is obviously extremely useful and successful in its niche, and I think the focus and investment there has been appropriate. The itch I was trying to scratch has to do with lowering the bar for production engineers to work with bayesian models,
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and in that context, *any* non-standard language is huge roadbump. The dependency on the gcc toolchain is also a (not insurmountable, but real) barrier to deployment.
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I see. So I guess to summarize the Stan perspective (as best I can): functional is not strictly more elegant than imperative, learning a C derivative is the least of a budding statistician's problems, and inference algorithms are probably not meant to be deployed (insights are).
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My personal views on those issues have definitely shifted over time (not sure where I'm at right now). Deployment is perhaps most arguable - their view stems from a fairly sturdy belief that inference algorithms aren't perfect and diagnostics should be inspected with ~every fit.
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Again, I think Stan made the right choices for its audience. I agree that it comes down to deployment. My question is, *if* you decided to deploy inference at scale, *then* what would you want? I do think a familiar production environment is part of that.
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Functional vs imperative isn’t that interesting a question to me here aside from the case where you already have engineers who are used to working in a particular environment and paradigm - at which point being as native to that env as possible is a big win.
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