Skip to content
Archive of entries posted by

The fundamental abstractions underlying BUGS and Stan as probabilistic programming languages

Probabilistic programming languages I think of BUGS and Stan as probabilistic programming languages because their variables may be used to denote random variables, with function application doing the right thing in terms of propagating randomness (usually encoding uncertainty in a Bayesian setting). They are not probabilistic programming languages that provide an object language for inference; […]

mc-stan.org down again (and up again)

[update: back up again 20 minutes later. sorry for all the churn and sorry again it went down.] My fault again. Really sorry about this. I’m actually on a real vacation for the first time in two years and not checking my email regularly and not checking my junk email at all. This time, PairNic […]

Stan Weekly Roundup, 25 August 2017

This week, the entire Columbia portion of the Stan team is out of the office and we didn’t have an in-person/online meeting this Thursday. Mitzi and I are on vacation, and everyone else is either teaching, TA-ing, or attending the Stan course. Luckily for this report, there’s been some great activity out of the meeting […]

Stan Weekly Roundup, 18 August 2017

Summer? What summer? Stan 2.17 is coming and there’s work to be done. Sebastian Weber has been making huge strides in adding MPI parallel autodiff to the math library (with design maturing for Stan itself and the library interfaces). Ongoing discusions on the Discourse forum and prototypes for a function to add to the Stan […]

mc-stan.org down & single points of failure

[update: back up. whew. back to our regularly scheduled programming.] [update: just talked to our registrar on the phone and they say it’ll probably take an hour or two for the DNS to catch up again, but then everything should be OK. I would highly recommend PairNIC—their support was awesome.] mc-stan.org is down because I […]

Stan Weekly Roundup, 11 August 2017

This week, more Stan! Charles Margossian is rock star of the week, finishing off the algebraic solver math library fixture and getting all plumbed through Stan and documented. Now you can solve nonlinear sets of equations and get derivatives with the implicit function theorem all as part of defining your log density. There is a […]

Stan Weekly Roundup, 3 August 2017

You’d almost think we were Europeans based on how much we’ve slowed down over the summer. Imad Ali, Jonah Gabry, and Ben Goodrich finished the online pkgdown-style documentation for all the Stan Development Team supported R packages. They can be accessed via http://mc-stan.org/(package_name), e.g., rstan: http://mc-stan.org/rstan rstanarm: http://mc-stan.org/rstanarm shinystan: http://mc-stan.org/shinytan loo: http://mc-stan.org/loo bayesplot: http://mc-stan.org/bayesplot The […]

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 […]

Stan Weekly Roundup, 21 July 2017

It was another productive week in Stan land. The big news is that Jonathan Auerbach, Tim Jones, Susanna Makela, Swupnil Sahai, and Robin Winstanley won first place in a New York City competition for predicting elementary school enrollment. Jonathan told me, “I heard 192 entered, and there were 5 finalists….Of course, we used Stan (RStan […]

Animating a spinner using ggplot2 and ImageMagick

It’s Sunday, and I [Bob] am just sitting on the couch peacefully ggplotting to illustrate basic sample spaces using spinners (a trick I’m borrowing from Jim Albert’s book Curve Ball). There’s an underlying continuous outcome (i.e., where the spinner lands) and a quantization into a number of regions to produce a discrete outcome (e.g., “success” […]

Stan Weekly Roundup, 14 July 2017

Another week, another bunch of Stan updates. Kevin Van Horn and Elea McDonnell Feit put together a tutorial on Stan [GitHub link] that covers linear regression, multinomial logistic regression, and hierarchical multinomial logistic regression. Andrew has been working on writing up our “workflow”. That includes Chapter 1, Verse 1 of Bayesian Data Analysis of (1) […]

Stan Weekly Roundup, 7 July 2017

Holiday weekend, schmoliday weekend. Ben Goodrich and Jonah Gabry shipped RStan 2.16.2 (their numbering is a little beyond base Stan, which is at 2.16.0). This reintroduces error reporting that got lost in the 2.15 refactor, so please upgrade if you want to debug your Stan programs! Joe Haupt translated the JAGS examples in the second […]

Stan Weekly Roundup, 30 June 2017

Here’s some things that have been going on with Stan since the last week’s roundup Stan® and the logo were granted a U.S. Trademark Registration No. 5,222,891 and a U.S. Serial Number: 87,237,369, respectively. Hard to feel special when there were millions of products ahead of you. Trademarked names are case insensitive and they required […]

Stan®

Update: Usage guidelines See: Stan trademark usage guide. We basically just followed Apache’s lead. It’s official “Stan” is now a registered trademark. For those keeping score, it’s U.S. Trademark Registration No. 5,222,891 [USPTO] The Stan logo (see image below) is also official U.S. Trademark Serial No. #87,237,369 [USPTO] No idea why there are serial numbers […]

Stan Weekly Roundup, 23 June 2017

Lots of activity this week, as usual. * Lots of people got involved in pushing Stan 2.16 and interfaces out the door; Sean Talts got the math library, Stan library (that’s the language, inference algorithms, and interface infrastructure), and CmdStan out, while Allen Riddell got PyStan 2.16 out and Ben Goodrich and Jonah Gabry are […]

Stan Weekly Roundup, 16 June 2017

We’re going to be providing weekly updates for what’s going on behind the scenes with Stan. Of course, it’s not really behind the scenes, because the relevant discussions are at stan-dev GitHub organization: this is the home of all of our source repos; design discussions are on the Stan Wiki Stan Discourse Groups: this is […]

Hello, world! Stan, PyMC3, and Edward

Being a computer scientist, I like to see “Hello, world!” examples of programming languages. Here, I’m going to run down how Stan, PyMC3 and Edward tackle a simple linear regression problem with a couple of predictors. No, I’m not going to take sides—I’m on a fact-finding mission. We (the Stan development team) have been trying […]

Design top down, Code bottom up

Top-down design means designing from the client application programmer interface (API) down to the code. The API lays out a precise functional specification, which says what the code will do, not how it will do it. Coding bottom up means coding the lowest-level foundations first, testing them, then continuing to build. Sometimes this requires dropping […]

Fitting hierarchical GLMs in package X is like driving car Y

Given that Andrew started the Gremlin theme, I thought it would only be fitting to link to the following amusing blog post: Chris Brown: Choosing R packages for mixed effects modelling based on the car you drive (on the seascape models blog) It’s exactly what it says on the tin. I won’t spoil the punchline, […]

Bayesian Posteriors are Calibrated by Definition

Time to get positive. I was asking Andrew whether it’s true that I have the right coverage in Bayesian posterior intervals if I generate the parameters from the prior and the data from the parameters. He replied that yes indeed that is true, and directed me to: Cook, S.R., Gelman, A. and Rubin, D.B. 2006. […]