Blog Archives

D&D 5e: Probabilities for Advantage and Disadvantage

July 12, 2014
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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 […] The post D&D 5e: Probabilities for Advantage and Disadvantage appeared first on Statistical Modeling,…

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Grand Opening: The Stan Shop

July 5, 2014
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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 […] The post Grand Opening: The Stan Shop appeared first on Statistical Modeling, Causal Inference,…

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Useless Algebra, Inefficient Computation, and Opaque Model Specifications

June 28, 2014
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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 […] The post Useless Algebra, Inefficient Computation, and Opaque Model Specifications appeared first on Statistical…

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(Py, R, Cmd) Stan 2.3 Released

June 26, 2014
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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 […] The post (Py, R, Cmd) Stan 2.3 Released appeared first on Statistical Modeling, Causal…

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Stan is Turing Complete. So what?

June 12, 2014
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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 […] The post Stan is Turing Complete. So what? appeared first on Statistical Modeling, Causal…

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Stan (& JAGS) Tutorial on Linear Mixed Models

May 4, 2014
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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: […] The post Stan (& JAGS) Tutorial on Linear Mixed Models appeared first on Statistical…

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

March 10, 2014
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[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.] […]The post Stan Model of the Week: PK Calculation of IV and Oral Dosing appeared…

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Running into a Stan Reference by Accident

March 3, 2014
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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 […]The post Running into a Stan Reference by Accident appeared first on Statistical Modeling, Causal…

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Stupid R Tricks: Random Scope

January 29, 2014
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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 […]The post Stupid R Tricks: Random Scope appeared first on Statistical Modeling, Causal Inference, and…

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Mailing List Degree-of-Difficulty Difficulty

January 20, 2014
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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 […]The post Mailing List Degree-of-Difficulty Difficulty appeared first on Statistical Modeling, Causal Inference, and Social…

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