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Archive of posts filed under the Stan category.

Item-response and ideal point models

To continue from today’s class, here’s what we’ll be discussing next time: – Estimating the direction and the magnitude of the discrimination parameters. – How to tell when your data don’t fit the model. – When does ideal-point modeling make a difference? Comparing ideal-point estimates to simple averages of survey responses. P.S. Unlike the previous […]

A silly little error, of the sort that I make every day

Ummmm, running Stan, testing out a new method we have that applies EP-like ideas to perform inference with aggregate data—it’s really cool, I’ll post more on it once we’ve tried everything out and have a paper that’s in better shape—anyway, I’m starting with a normal example, a varying-intercept, varying-slope model where the intercepts have population […]

New research in tuberculosis mapping and control

Mapping and control. Or, as we would say, descriptive and causal inference. Jon Zelner informs os about two ongoing research projects: 1. TB Hotspot Mapping: Over the summer, I [Zelner] put together a really simple R package to do non-parametric disease mapping using the distance-based mapping approach developed by Caroline Jeffery and Al Ozonoff at […]

Stan meetup in NYC on Tuesday

The next Stan meetup in NYC is on Tuesday, 4/7/2015. If you have installation issues, modeling trouble, or just want to pick some of the developers’ brains, show up. Free. Registration required:   P.S. Boston, Stan meetups are coming your way.

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 […]

First World problems: Stan edition

Jonah writes: First of all, every time I type ‘shinyapps’ the autocorrect replaces it with ‘chin-ups’. It was amusing but now it’s just annoying. You’d think Apple would have added the ability for the autocorrect to notice that I keep changing it back to “shinyapps” without making me manually add it as an exception. That’s […]

My talk tomorrow (Thurs) at MIT political science: Recent challenges and developments in Bayesian modeling and computation (from a political and social science perspective)

It’s 1pm in room E53-482. I’ll talk about the usual stuff (and some of this too, I guess).

One simple trick to make Stan run faster

Did you know that Stan automatically runs in parallel (and caches compiled models) from R if you do this: source(“”) It’s from Stan core developer Ben Goodrich. This simple line of code has changed my life. A factor-of-4 speedup might not sound like much, but, believe me, it is!

Introducing shinyStan

As a project for Andrew’s Statistical Communication and Graphics graduate course at Columbia, a few of us (Michael Andreae, Yuanjun Gao, Dongying Song, and I) had the goal of giving RStan’s print and plot functions a makeover. We ended up getting a bit carried away and instead we designed a graphical user interface for interactively exploring virtually […]

Upcoming Stan-related talks

If you’re in NYC or Sidney, there are some Stan-related talks in the next few weeks.   New York 25 February. Jonah Gabry: shinyStan: a graphical user interface for exploring Bayesian models after MCMC. Register Now: New York Open Statistical Programming Meetup. 12 March. Rob Trangucci: #5: Non-centered parameterization aka the “Matt trick.” Register Now: Stan […]