Stan Weekly Roundup, 28 July 2017

Here’s the roundup for this past week.

• Michael Betancourt added case studies for methodology in both Python and R, based on the work he did getting the ML meetup together:
  • RStan workflow
  • PyStan workflow
• Michael Betancourt, along with Mitzi Morris, Sean Talts, and Jonah Gabry taught the women in ML workshop at Viacom in NYC and there were 60 attendees working their way up from simple linear regression, through Poisson regression to GPs.
• Ben Goodrich has been working on new R^2 analyses and priors, as well as the usual maintenance on RStan and RStanArm.
• Aki Vehtari was at the summer school in Valencia teaching Stan.
• Aki has also been kicking off planning for StanCon in Helsinki 2019. Can’t believe we’re planning that far ahead!
• Sebastian Weber was in Helsinki giving a talk on Stan, but there weren’t many Bayesians there to get excited about Stan; he’s otherwise been working with Aki on variable selection.
• Imad Ali is finishing up the spatial models in RStanArm and moving on to new classes of models (we all know his goal is to model basketball, which is a very spatially continuous game!).
• Ben Bales has been working on generic append array funcitons and vectorizing random number geneators. We learned his day job was teaching robotics with lego to mechanical engineering students!
• Charles Margossian is finishing up the algebraic solvers (very involved autodiff issues there, as with the ODE solvers) and wrapping up a final release of Torsten before he moves to Columbia to start the Ph.D. program in stats. He’s also writing the mixed solver paper with feedback from Michael Betancourt and Bill Gillespie.
• Mitzi Morris added runtime warning messages for problems arising in declarations, which inadvertently fixed another bug arising for declarations with sizes for which constraints couldn’t be satisfied (as in size zero simplexes).
• Miguel Benito, along with Mitzi Morris and Dan Simpson, with input from Michael Betancourt and Andrew Gelman, now have spatial models with matching results across GeoBUGS, INLA, and Stan. They further worked on better priors for Stan so that it’s now competitive in fitting; turns out the negative effect of the sum-to-zero constraint on the spatial random effects had a greater negative effect on the geometry than a positive effect on identifiability.
• Michael Andreae resubmitted papers with Ben Goodrich and Jonah Gabry and is working on some funding prospects.
• Sean Talts (with help from Daniel Lee) has most of the C++11/C++14 dev ops in place so we’ll be able to start using all those cool toys.
• Sean Talts and Michael Betancourt with some help from Mitzi Morris, have been doing large-scale Cook-Gelman-Rubin evaluations for simple and hierarchical models and finding some surprising results (being discussed on Discourse). My money’s on them getting to the bottom of what’s going on soon; Dan Simpson’s jumping in to help out on diagnostics, in the same thread on Discourse.
• Aki Vehtari reports that Amazon UK (with Neil Lawrence and crew) are using Stan, so we expect to see some more GP activity at some point.
• We spent a long time discussing how to solve the multiple translation unit problems. It looks at first glance like Eigen just inlines every function and that may also work for us (if a function is declared inline, it may be defined in multiple translation units).
• Solène Desmée, along with France Mentré and others have been fitting time-to-event models in Stan and have a new open-access publication, Nonlinear joint models for individual dynamic prediction of risk of death using Hamiltonian Monte Carlo: application to metastatic prostate cancer. You may remember France as the host of last year’s PK/PD Stan conference in Paris.

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