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D&D 5e: Probabilities for Advantage and Disadvantage

The new rules for D&D 5e (formerly known as D&D Next) are finally here: Dungeons & Dragons, 5th Edition: Basic Rules D&D 5e introduces a new game mechanic, advantage and disadvantage. Basic d20 Rules Usually, players roll a 20-sided die (d20) to resolve everyting from attempts at diplomacy to hitting someone with a sword. Each […]

Grand Opening: The Stan Shop

I finally put together a shop so everyone can order Stan t-shirts and mugs: The Stan Shop The art’s by Michael Malecki. The t-shirts and mugs are printed on demand by Spreadshirt. I tried out a sample and the results are great and have held up to machine washing and drying. There’s a markup of […]

Useless Algebra, Inefficient Computation, and Opaque Model Specifications

I (Bob, not Andrew) doubt anyone sets out to do algebra for the fun of it, implement an inefficient algorithm, or write a paper where it’s not clear what the model is. But… Why not write it in BUGS or Stan? Over on the Stan users group, Robert Grant wrote Hello everybody, I’ve just been […]

(Py, R, Cmd) Stan 2.3 Released

We’re happy to announce RStan, PyStan and CmdStan 2.3. Instructions on how to install at: http://mc-stan.org/ As always, let us know if you’re having problems or have comments or suggestions. We’re hoping to roll out the next release a bit quicker this time, because we have lots of good new features that are almost ready […]

Stan is Turing Complete. So what?

This post is by Bob Carpenter. Stan is Turing complete! There seems to a persistent misconception that Stan isn’t Turing complete.1, 2 My guess is that it stems from Stan’s (not coincidental) superficial similarity to BUGS and JAGS, which provide directed graphical model specification languages. Stan’s Turing completeness follows from its support of array data […]

Stan (& JAGS) Tutorial on Linear Mixed Models

Shravan Vasishth sent me an earlier draft of this tutorial he co-authored with Tanner Sorensen. I liked it, asked if I could blog about it, and in response, they’ve put together a convenient web page with links to the tutorial PDF, JAGS and Stan programs, and data: Fitting linear mixed models using JAGS and Stan: […]

Stan Model of the Week: PK Calculation of IV and Oral Dosing

[Update: Revised given comments from Wingfeet, Andrew and germo. Thanks! I'd mistakenly translated the dlnorm priors in the first version --- amazing what a difference the priors make. I also escaped the less-than and greater-than signs in the constraints in the model so they're visible. I also updated to match the thin=2 output of JAGS.] […]

Running into a Stan Reference by Accident

We were talking about parallelizing MCMC and I came up with what I thought was a neat idea for parallelizing MCMC (sample with fractional prior, average samples on a per-draw basis). But then I realized this approach could get the right posterior mean or right posterior variance, but not both, depending on how the prior […]

Stupid R Tricks: Random Scope

Andrew and I have been discussing how we’re going to define functions in Stan for defining systems of differential equations; see our evolving ode design doc; comments welcome, of course. About Scope I mentioned to Andrew I would prefer pure lexical, static scoping, as found in languages like C++ and Java. If you’re not familiar […]

Mailing List Degree-of-Difficulty Difficulty

The Difficulty with Difficult Questions Andrew’s commented during our Stan meetings that he’s observed that when a user sends an easy question to a mailing list, it gets answered right away, whereas difficult questions often languish with no answers. These difficult questions usually come from power users with real issues, whereas the simple questions are […]