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Archive of posts filed under the Stan category.

Stan in St. Louis this Friday

This Friday afternoon I (Jonah) will be speaking about Stan at Washington University in St. Louis. The talk is open to the public, so anyone in the St. Louis area who is interested in Stan is welcome to attend. Here are the details: Title: Stan: A Software Ecosystem for Modern Bayesian Inference Jonah Sol Gabry, […]

Fitting hierarchical GLMs in package X is like driving car Y

Given that Andrew started the Gremlin theme (the car in the image at the right), I thought it would only be fitting to link to the following amusing blog post: Chris Brown: Choosing R packages for mixed effects modelling based on the car you drive (on the seascape models blog) It’s exactly what it says […]

Stacking, pseudo-BMA, and AIC type weights for combining Bayesian predictive distributions

This post is by Aki. We have often been asked in the Stan user forum how to do model combination for Stan models. Bayesian model averaging (BMA) by computing marginal likelihoods is challenging in theory and even more challenging in practice using only the MCMC samples obtained from the full model posteriors. Some users have […]

Tech company wants to hire Stan programmers!

Ittai Kan writes: I started life as an academic mathematician (chaos theory) but have long since moved into industry. I am currently Chief Scientist at Afiniti, a contact center routing technology company that connects agent and callers on the basis of various factors in order to globally optimize the contact center performance. We have 17 […]

“Scalable Bayesian Inference with Hamiltonian Monte Carlo” (Michael Betancourt’s talk this Thurs at Columbia)

Scalable Bayesian Inference with Hamiltonian Monte Carlo Despite the promise of big data, inferences are often limited not by sample size but rather by systematic effects. Only by carefully modeling these effects can we take full advantage of the data—big data must be complemented with big models and the algorithms that can fit them. One […]

Running Stan with external C++ code

Ben writes: Starting with the 2.13 release, it is much easier to use external C++ code in a Stan program. This vignette briefly illustrates how to do so.

Prediction model for fleet management

Chang writes: I am working on a fleet management system these days: basically, I am trying to predict the usage ‘y’ of our fleet in a zip code in the future. We have some factors ‘X’, such as number of active users, number of active merchants etc. If I can fix the time horizon, the […]

2 Stan job postings at Columbia (links fixed)

1. Stan programmer. This is the “Stan programmers” position described here. 2. Stan project development. This is the Stan business developer/grants manager described here. To apply, click on the first link for each position above (the academicjobs.columbia.edu site) and follow the instructions. P.S. In first version of this post I messed up the links. They’re […]

Mortality rate trends by age, ethnicity, sex, and state (link fixed)

There continues to be a lot of discussion on the purported increase in mortality rates among middle-aged white people in America. Actually an increase among women and not much change among men but you don’t hear so much about this as it contradicts the “struggling white men” story that we hear so much about in […]

Ensemble Methods are Doomed to Fail in High Dimensions

Ensemble methods By ensemble methods, I (Bob, not Andrew) mean approaches that scatter points in parameter space and then make moves by inteprolating or extrapolating among subsets of them. Two prominent examples are: Ter Braak’s differential evolution   Goodman and Weare’s walkers There are extensions and computer implementations of these algorithms. For example, the Python […]

Hey, we’re hiring a postdoc! To work on survey weighting! And imputation!

Here’s the ad: The Center on Poverty and Social Policy at the Columbia University School of Social Work and the Columbia Population Research Center are seeking a postdoctoral scholar with a PhD in economics, statistics, public policy, demography, social work, sociology, or a related discipline, to lead the development of survey weights and missing data imputations for the New York City […]

Expectation propagation as a way of life: A framework for Bayesian inference on partitioned data

After three years, we finally have an updated version of our “EP as a way of life” paper. Authors are Andrew Gelman, Aki Vehtari, Pasi Jylänki, Tuomas Sivula, Dustin Tran, Swupnil Sahai, Paul Blomstedt, John Cunningham, David Schiminovich, and Christian Robert. Aki deserves credit for putting this all together into a coherent whole. Here’s the […]

A fistful of Stan case studies: divergences and bias, identifying mixtures, and weakly informative priors

Following on from his talk at StanCon, Michael Betancourt just wrote three Stan case studies, all of which are must reads: Diagnosing Biased Inference with Divergences: This case study discusses the subtleties of accurate Markov chain Monte Carlo estimation and how divergences can be used to identify biased estimation in practice.   Identifying Bayesian Mixture […]

Facebook’s Prophet uses Stan

Sean Taylor, a research scientist at Facebook and Stan user, writes: I wanted to tell you about an open source forecasting package we just released called Prophet:  I thought the readers of your blog might be interested in both the package and the fact that we built it on top of Stan. Under the hood, […]

Stan Language Design History

Andrew’s proposal At our last Stan meeting, Andrew proposed allowing priors to be defined for parameters near where they are declared, as in: parameters { real mu; mu ~ normal(0, 1); real sigma; sigma ~ lognormal(0, 1); … I can see the pros and cons. The pro is that it’s easier to line things up […]

Research fellow, postdoc, and PhD positions in probabilistic modeling and machine learning in Finland

Probabilistic modeling and machine learning are strong in Finland. Now is your opportunity to join us in this cool country! There are several postdoc and research fellow positions open in probabilistic machine learning in Aalto University and University of Helsinki (deadline Marh 19). Some of the topics are related also to probabilistic programming and Stan […]

Exposure to Stan has changed my defaults: a non-haiku

Now when I look at my old R code, it looks really weird because there are no semicolons Each line of code just looks incomplete As if I were writing my sentences like this Whassup with that, huh Also can I please no longer do <- I much prefer = Please

Blind Spot

X pointed me to this news article reporting an increase in death rate among young adults in the United States: Selon une enquête publiée le 26 janvier par la revue scientifique The Lancet, le taux de mortalité des jeunes Américains âgés de 25 à 35 ans a connu une progression entre 1999 et 2014, alors […]

Accessing the contents of a stanfit object

I was just needing this. Then, lo and behold, I found it on the web. It’s credited to Stan Development Team but I assume it was written by Ben and Jonah. Good to have this all in one place.

Krzysztof Sakrejda speaks in NYC on Bayesian hierarchical survival-type model for Dengue infection

Daniel writes: Krzysztof Sakrejda is giving a cool talk next Tues 5:30-7pm downtown on a survival model for Dengue infection using Stan. If you’re interested, please register asap. Google is asking for the names for security by tomorrow morning.