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Archive of posts filed under the Stan category.

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 […]

Short course on Bayesian data analysis and Stan 23-25 Aug in NYC!

Jonah “ShinyStan” Gabry, Mike “Riemannian NUTS” Betancourt, and I will be giving a three-day short course next month in New York, following the model of our successful courses in 2015 and 2016. Before class everyone should install R, RStudio and RStan on their computers. (If you already have these, please update to the latest version […]

Make Your Plans for Stans (-s + Con)

This post is by Mike A friendly reminder that registration is open for StanCon 2018, which will take place over three days, from Wednesday January 10, 2018 to Friday January 12, 2018, at the beautiful Asilomar Conference Grounds in Pacific Grove, California. Detailed information about registration and accommodation at Asilomar, including fees and instructions, can be found on […]

Hey—here are some tools in R and Stan to designing more effective clinical trials! How cool is that?

In statistical work, design and data analysis are often considered separately. Sometimes we do all sorts of modeling and planning in the design stage, only to analyze data using simple comparisons. Other times, we design our studies casually, even thoughtlessly, and then try to salvage what we can using elaborate data analyses. It would be […]

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) […]

Sparse regression using the “ponyshoe” (regularized horseshoe) model, from Juho Piironen and Aki Vehtari

The article is called “Sparsity information and regularization in the horseshoe and other shrinkage priors,” and here’s the abstract: The horseshoe prior has proven to be a noteworthy alternative for sparse Bayesian estimation, but has previously suffered from two problems. First, there has been no systematic way of specifying a prior for the global shrinkage […]

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/NYC WiMLDS Workshop

On Saturday, July 22nd Mitzi Morris and I (Michael Betancourt) will be hosting a day-long Stan workshop for the NYC Women in Machine Learning & Data Science Meetup Group.  As with most of our workshops the emphasis will be on interactive exercises where everyone builds and running models in Stan.  We’ll start with the foundations […]

What is a pull request?

Bob explains: A pull request (PR) is the minimal publishable unit of open-source development. It’s a proposed change to the code base that we can then review. If you want to see how the sausage is made, follow this link. If you click on “files changed”, you’ll see what Sean is proposing doing with the […]

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 […]

Estimating Public Market Exposure of Private Capital Funds Using Bayesian Inference

I don’t know anything about this work by Luis O’Shea and Vishv Jeet—that is, I know nothing of public market exposure or private capital firms, and I don’t know anything about the model they fit, the data they used, or what information they had available for constructing and checking their model. But what I do […]

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 […]

SPEED: Parallelizing Stan using the Message Passing Interface (MPI)

Sebastian Weber writes: Bayesian inference has to overcome tough computational challenges and thanks to Stan we now have a scalable MCMC sampler available. For a Stan model running NUTS, the computational cost is dominated by gradient calculations of the model log-density as a function of the parameters. While NUTS is scalable to huge parameter spaces, […]

PhD student fellowship opportunity! in Belgium! to work with us! on the multiverse and other projects on improving the reproducibility of psychological research!!!

[image of Jip and Janneke dancing with a cat] Wolf Vanpaemel and Francis Tuerlinckx write: We at the Quantitative Psychology and Individual Differences, KU Leuven, Belgium are looking for a PhD candidate. The goal of the PhD research is to develop and apply novel methodologies to increase the reproducibility of psychological science. More information can […]

UK election summary

The Conservative party, led by Theresa May, defeated the Labour party, led by Jeremy Corbyn. The Conservative party got 42% of the vote, Labour got 40% of the vote, and all the other parties received 18% between them. The Conservatives ended up with 51.5% of the two-party vote, just a bit less than Hillary Clinton’s […]

Using external C++ functions with PyStan & radial velocity exoplanets

Dan Foreman-Mackey writes: I [Mackey] demonstrate how to use a custom C++ function in a Stan model using the Python interface PyStan. This was previously only possible using the R interface RStan (see an example here) so I hacked PyStan to make this possible in Python as well. . . . I have some existing […]

U.K. news article congratulates YouGov on using modern methods in polling inference

Mike Betancourt pointed me to this news article by Alan Travis that is refreshingly positive regarding the use of sophisticated statistical methods in analyzing opinion polls. Here’s Travis: Leading pollsters have described YouGov’s “shock poll” predicting a hung parliament on 8 June as “brave” and the decision by the Times to splash it on its […]

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 […]