This puzzle comes in three parts. There are some hints at the end. Part I: Constrained Parameter Definition Define a Stan program with a transformed matrix parameter d that is constrained to be a K by K distance matrix. Recall that a distance matrix must satisfy the definition of a metric for all i, j: […]

## 4 for 4.0 — The Latest JAGS

This post is by Bob Carpenter. I just saw over on Martyn Plummer’s JAGS News blog that JAGS 4.0 is out. Martyn provided a series of blog posts highlighting the new features: 1. Reproducibility: Examples will now be fully reproducible draw-for-draw and chain-for-chain with the same seed. (Of course, compiler, optimization level, platform, CPU, and […]

## You’ll never guess what’s been happening with PyStan and PyMC—Click here to find out.

PLEASE NOTE: This is a guest post by Llewelyn Richards-Ward. When there are two packages appearing to do the same thing, lets return to the Zen of Python which suggests that: There should be one—and preferably only one—obvious way to do it. Why is this particular mantra important? I think because the majority of users […]

## Stan PK/PD Tutorial at the American Conference on Pharmacometrics, 8 Oct 2015

Bill Gillespie, of Metrum, is giving a tutorial next week at ACoP: Getting Started with Bayesian PK/PD Modeling Using Stan: Practical use of Stan and R for PK/PD applications Thursday 8 October 2015, 8 AM — 5 PM, Crystal City, VA This is super cool for us, because Bill’s not one of our core developers […]

## Solution to Stan Puzzle 1: Inferring Ability from Streaks

If you missed it the first time around, here’s a link to: Stan Puzzle 1: Inferring Ability from Streaks First, a hat-tip to Mike, who posted the correct answer as a comment. So as not to spoil the surprise for everyone else, Michael Betancourt (different Mike), emailed me the answer right away (as he always […]

## Stan Puzzle #1: Inferring Ability from Streaks

Inspired by X’s blog’s Le Monde puzzle entries, I have a little Stan coding puzzle for everyone (though you can solve the probabilty part of the coding problem without actually knowing Stan). This almost (heavy emphasis on “almost” there) makes me wish I was writing exams. Puzzle #1: Inferring Ability from Streaks Suppose a player […]

## PK/PD Talk with Stan — Thu 8 Oct, 10:30 AM at Columbia: Improved confidence intervals and p-values by sampling from the normalized likelihood

Sebastian Ueckert and France Mentré are swinging by to visit the Stan team at Columbia and Sebastian’s presenting the following talk, to which everyone is invited. Improved confidence intervals and p-values by sampling from the normalized likelihood Sebastian Ueckert (1,2), Marie-Karelle Riviere (1), France Mentré (1) (1) IAME, UMR 1137, INSERM and University Paris Diderot, […]

## Stan Meetup Talk in Ann Arbor this Wednesday (5 Aug 2015)

I (Bob) will be presenting an overview of (R)Stan at the Ann Arbor R User Group meetup this Wednesday night (5 August 2015) at 7 PM. To see the abstract and register to attend: RStan: Statistical Modeling Made Easy with Bob Carpenter Wednesday, Aug 5, 2015, 7:00 PM Barracuda Networks317 Maynard St Ann Arbor, MI […]

## Stan 2.7 (CRAN, variational inference, and much much more)

Stan 2.7 is now available for all interfaces. As usual, everything you need can be found starting from the Stan home page: http://mc-stan.org/ Highlights RStan is on CRAN!(1) Variational Inference in CmdStan!!(2) Two new Stan developers!!! A whole new logo!!!! Math library with autodiff now available in its own repo!!!!! (1) Just doing install.packages(“rstan”) isn’t […]

## Don’t put your whiteboard behind your projection screen

Daniel, Andrew, and I are on our second day of teaching, and like many places, Memorial Sloan-Kettering has all their classrooms set up with a whiteboard placed directly behind a projection screen. This gives us a sliver of space to write on without pulling the screen up and down. If you have any say in […]

## Introducing StataStan

Thanks to Robert Grant, we now have a Stata interface! For more details, see: Robert Grant’s Blog: Introducing StataStan Jonah and Ben have already kicked the tires, and it works. We’ll be working on it more as time goes on as part of our Institute of Education Sciences grant (turns out education researchers use […]

## JuliaCon 2015 (24–27 June, Boston-ish)

JuliaCon is coming to Cambridge, MA the geek capital of the East Coast: 24–27 June. Here’s the conference site with program. I (Bob) will be giving a 10 minute “lightning talk” on Stan.jl, the Julia interface to Stan (built by Rob J. Goedman — I’m just pinch hitting because Rob couldn’t make it). The uptake […]

## New Book: Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

Fränzi and Tobias‘s book is now real: Fränzi Korner-Nievergelt, Tobias Roth, Stefanie von Felten, Jérôme Guélat, Bettina Almasi, and Pius Korner-Nievergelt (2015) Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan. Academic Press. This is based in part on the in-person tutorials that they and the other authors have been giving […]

## What do CERN, the ISS, and Stephen Fry have in Common?

You’ll have to read the New Yorker article on Richard M. Stallman and the The GNU Manifesto by Maria Bustillos to find out! And what’s up with Tim O’Reilly’s comments about the Old Testment vs. New Testament? That’s an ad hominem attack of the highest order, guaranteed to get the Judeo-Christians even more riled […]

## Stan Down Under

I (Bob, not Andrew) am in Australia until April 30. I’ll be giving some Stan-related and some data annotation talks, several of which have yet to be concretely scheduled. I’ll keep this page updated with what I’ll be up to. All of the talks other than summer school will be open to the public (the […]

## Stan 2.6.0 Released

We’re happy to announce the release of Stan 2.6, including RStan, PyStan, CmdStan; it will also work with the existing Stan.jl and MatlabStan. Although there is some new functionality (hence the minor version bump), this is primarily a maintenance release. It fixes all of the known memory issues with Stan 2.5.0 and improves overall speed […]

*Bayesian Cognitive Modeling* Models Ported to Stan

Hats off for Martin Šmíra, who has finished porting the models from Michael Lee and Eric-Jan Wagenmakers’ book Bayesian Cognitive Modeling to Stan. Here they are: Bayesian Cognitive Modeling: Stan Example Models Martin managed to port 54 of the 57 models in the book and verified that the Stan code got the same answers as […]

## Soil Scientists Seeking Super Model

I (Bob) spent last weekend at Biosphere 2, collaborating with soil carbon biogeochemists on a “super model.” Model combination and expansion The biogeochemists (three sciences in one!) have developed hundreds of competing models and the goal of the workshop was to kick off some projects on putting some of them together intos wholes that are […]

## No, Michael Jordan didn’t say that!

The names are changed, but the song remains the same. First verse. There’s an article by a journalist, The odds, continually updated, by F.D. Flam in the NY Times to which Andrew responded in blog form, No, I didn’t say that, by Andrew Gelman, on this blog. Second verse. There’s an article by a journalist, […]

## Stan 2.5, now with MATLAB, Julia, and ODEs

As usual, you can find everything on the Stan Home Page. Drop us a line on the stan-users group if you have problems with installs or questions about Stan or coding particular models. New Interfaces We’d like to welcome two new interfaces: MatlabStan by Brian Lau, and Stan.jl (for Julia) by Rob Goedman. The new […]