NYC Meetup Thursday: Under the hood: Stan’s library, language, and algorithms

January 11, 2019
By

[This article was first published on R – Statistical Modeling, Causal Inference, and Social Science, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

I (Bob, not Andrew!) will be doing a meetup talk this coming Thursday in New York City. Here’s the link with registration and location and time details (summary: pizza unboxing at 6:30 pm in SoHo):

After summarizing what Stan does, this talk will focus on how Stan is engineered. The talk follows the organization of the Stan software.

Stan math library: differentiable math and stats functions, template metaprorgrams to manage constants and vectorization, matrix derivatives, and differential equation derivatives.

Stan language: block structure and execution, unconstraining variable transforms and automatic Jacobians, transformed data, parameters, and generated quantities execution.

Stan algorithms: Hamiltonian Monte Carlo and the no-U-turn sampler (NUTS), automatic differentiation variational inference (ADVI).

Stan infrastructure and process: Time permitting, I can also discuss Stan’s developer process, how the code repositories are organized, and the code review and continuous integration process for getting new code into the repository

Slides

I realized I’m missing a good illustration of NUTS and how it achieves detailed balance and preferentially selects positions on the Hamiltonian trajectory toward the end of the simulated dynamics (to minimize autocorrelation in the draws). It was only an hour, so I skipped the autodiff section and scalable algorithms section and jumped to the end. I’ll volunteer do another meetup with the second half of the talk.

To leave a comment for the author, please follow the link and comment on their blog: R – Statistical Modeling, Causal Inference, and Social Science.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)