“I just wanted to say that for the first time in three (4!?) years of efforts, I have a way to estimate my model. . . .”

After attending a Stan workshop given by Charles Margossian at McGill University, Chris Barrington-Leigh wrote:

I just wanted to say that for the first time in three (4!?) years of efforts, I have a way to estimate my model. Your workshop helped me and pushed me to be persistent enough to code up my model. After finally getting it to work late last week in RStan, I’ve even switched over to PyStan now, which means I’m as happy as a clam. Quite giddy, actually!

I can’t believe I don’t even need to code in in all those Jacobians and Hessians I computed analytically last summer…

Thank you! I’m so excited. I have a tonne of reading to do, I suppose, to build up a deeper knowledge of Bayesian approaches, but in the mean time I should have two papers on this stuff in no time, haha!

I’ve been saying to other people that I think this whole phenomenon of top statisticians making this stuff accessible to mortals (and to a wide variety of uses) by putting it all in open source and so quickly from new research to wide availability … is really cool. Like Wikipedia, and like OSS more generally. It’s a bright light.

It’s wonderful to hear this sort of thing. Indeed, sometime in academia less credit is given for (a) teaching, (b) software development, and (c) applied work. So it’s great to hear some appreciation for a combination of these three.

Also, regarding “for the first time in years, I have a way to estimate my model”: this has happened to me too! My colleagues and I have fit models in our applied work (for example, here) that we never would’ve even tried in the pre-Stan era.