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Archive of posts filed under the Stan category.

Cross-validation, LOO and WAIC for time series

This post is by Aki. Jonah asked in Stan users mailing list Suppose we have J groups and T time periods, so y[t,j] is the observed value of y at time t for group j. (We also have predictors x[t,j].) I’m wondering if WAIC is appropriate in this scenario assuming that our interest in predictive accuracy is for […]

Stan comes through . . . again!

Erikson Kaszubowski writes in: I missed your call for Stan research stories, but the recent post about stranded dolphins mentioned it again. When I read about the Crowdstorming project in your blog, I thought it would be a good project to apply my recent studies in Bayesian modeling. The project coordinators shared a big dataset […]

Artist needed!

We have some great ideas but none of us can draw. We need your help with designs and art for any or all of these projects: 1. “Gone Fishing” T-shirt A person is standing in a boat, fishing. The lake is full, not of fish but of little numbers: “.14″, “.31″, “.08″, etc etc. And […]

Planning my class for this semester: Thinking aloud about how to move toward active learning?

I’m teaching two classes this semester: – Design and Analysis of Sample Surveys (in the political science department, but the course has lots of statistics content); – Statistical Communication and Graphics (in the statistics department, but last time I taught it, many of the students were from other fields). I’ve taught both classes before. I […]

Expectation propagation as a way of life

Aki Vehtari, Pasi Jylänki, Christian Robert, Nicolas Chopin, John Cunningham, and I write: We revisit expectation propagation (EP) as a prototype for scalable algorithms that partition big datasets into many parts and analyze each part in parallel to perform inference of shared parameters. The algorithm should be particularly efficient for hierarchical models, for which the […]

Stan at NIPS 2014

For those in Montreal a few of the Stan developers will giving talks at the NIPS workshops this week.  On Saturday at 9 AM I’ll be talking about the theoretical foundations of Hamiltonian Monte Carlo at the Riemannian Geometry workshop ( while Dan will be talking about Stan at the Software Engineering workshop ( Saturday […]

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 […]

Stan hack session at Columbia on Saturday

[this post is by Daniel] For those of you in NYC this Saturday, we’re having a Stan hack session from 11 am – 5 pm. A lot of the Stan developers will be around. It’s free, but registration required. See link below. Bring a laptop, some data, and a model you want to fit. Or […]

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 […]

Stan hits bigtime

First Wikipedia, then the Times (featuring Yair Ghitza), now Slashdot (featuring Allen “PyStan” Riddell). Just get us on Gawker and we’ll have achieved total media saturation. Next step, backlash. Has Stan jumped the shark? Etc. (We’d love to have a “jump the shark” MCMC algorithm but I don’t know if or when we’ll get there. […]