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Archive of posts filed under the Stan category.

Analyzing New Zealand fatal traffic crashes in Stan with added open-access science

Open-access science I’ll get to the meat of this post in a second, but I just wanted to highlight how the study I’m about to talk about was done in the open and how that helped everyone. Tim Makarios read the study and responded in the blog comments, Hold on. As I first skimmed this […]

Baseball, apple pie, and Stan

Ben sends along these two baseball job ads that mention experience with Stan as a preferred qualification: St. Louis Cardinals Baseball Development Analyst Tampa Bay Rays Baseball Research and Development Analyst

Stan case studies

Following up on recent posts here and here, I thought I’d post a list of all the Stan case studies we have so far. 2017: Modeling Loss Curves in Insurance with RStan, by Mick Cooney Splines in Stan, by Milad Kharratzadeh Spatial Models in Stan: Intrinsic Auto-Regressive Models for Areal Data, by Mitzi Morris The […]

Mick Cooney: case study on modeling loss curves in insurance with RStan

This is great. Thanks, Mick! All the Stan case studies are here.

Postdoc in Finland and NY to work on probabilistic inference and Stan!

I (Aki) got 2 year funding to hire a postdoc to work on validation of probabilistic inference approaches and model selection in Stan. Work would be done with Stan team in Aalto, Helsinki and Columbia, New York. We probably have PhD positions, too. The funding is part of the joint project with Antti Honkela and […]

Halifax, NS, Stan talk and course Thu 19 Oct

Halfiax, here we come. I (Bob, not Andrew) am going to be giving a talk on Stan and then Mitzi and I will be teaching a course on Stan after that. The public is invited, though space is limited for the course. Here are details if you happen to be in the Maritime provinces. TALK: […]

Workshop on Interpretable Machine Learning

Andrew Gordon Wilson sends along this conference announcement: NIPS 2017 Symposium Interpretable Machine Learning Long Beach, California, USA December 7, 2017 Call for Papers: We invite researchers to submit their recent work on interpretable machine learning from a wide range of approaches, including (1) methods that are designed to be more interpretable from the start, […]

Partial pooling with informative priors on the hierarchical variance parameters: The next frontier in multilevel modeling

Ed Vul writes: In the course of tinkering with someone else’s hairy dataset with a great many candidate explanatory variables (some of which are largely orthogonal factors, but the ones of most interest are competing “binning” schemes of the same latent elements). I wondered about the following “model selection” strategy, which you may have alluded […]

Splines in Stan; Spatial Models in Stan !

Two case studies: Splines in Stan, by Milad Kharratzadeh. Spatial Models in Stan: Intrinsic Auto-Regressive Models for Areal Data, by Mitzi Morris. This is great. Thanks, Mitzi! Thanks, Milad!

Tenure-Track or Tenured Prof. in Machine Learning in Aalto, Finland

This job advertisement for a position in Aalto, Finland, is by Aki We are looking for a professor to either further strengthen our strong research fields, with keywords including statistical machine learning, probabilistic modelling, Bayesian inference, kernel methods, computational statistics, or complementing them with deep learning. Collaboration with other fields is welcome, with local opportunities […]

Stan Roundup, 6 October 2017

I missed last week and almost forgot to add this week’s. Jonah Gabry returned from teaching a one-week course for a special EU research institute in Spain. Mitzi Morris has been knocking out bug fixes for the parser and some pull requests to refactor the underlying type inference to clear the way for tuples, sparse […]

Getting the right uncertainties when fitting multilevel models

Cesare Aloisi writes: I am writing you regarding something I recently stumbled upon in your book Data Analysis Using Regression and Multilevel/Hierarchical Models which confused me, in hopes you could help me understand it. This book has been my reference guide for many years now, and I am extremely grateful for everything I learnt from […]

Stan Weekly Roundup, 22 September 2017

This week (and a bit from last week) in Stan: Paul-Christian Bürkner‘s paper on brms (a higher-level interface to RStan, which preceded rstanarm and is still widely used and recommended by our own devs) was just published as a JStatSoft article. If you follow the link, the abstract explains what brms does. Ben Goodrich and […]

Call for papers: Probabilistic Programming Languages, Semantics, and Systems (PPS 2018)

I’m on the program committee and they say they’re looking to broaden their horizons this year to include systems like Stan. The workshop is part of POPL, the big programming language theory conference. Here’s the official link PPS 2018 home page Call for extended abstracts (2 pages) The submissions are two-page extended abstracts and the […]

Stan Course in Newcastle, United Kingdom!

(this post is by Betancourt) The growth of Stan has afforded the core team many opportunities to give courses, to both industrial and academic audiences and at venues  across the world.  Regrettably we’re not always able to keep up with demand for new courses, especially outside of the United States, due to our already busy schedules. […]

Extended StanCon 2018 Deadline!

(this post is by Betancourt) We received an ensemble of exciting submissions for StanCon2018, but some of our colleagues requested a little bit of extra time to put the finishing touches on their submissions.  Being the generous organizers that we are, we have decided to extend the submission deadline for everyone by two weeks. Contributed submissions […]

Job openings at online polling company!

Kyle Dropp of online polling firm Morning Consult says they are hiring a bunch of mid-level data scientists and software engineers at all levels: About Morning Consult: We are interviewing about 10,000 adults every day in the U.S. and ~20 countries, we have worked with 150+ Fortune 500 companies and industry associations and we are […]

The StanCon Cometh

(In a stunning deviation from the norm, this post is not by Andrew or Dan, but Betancourt!) Some important dates for StanCon2018 are rapidly approaching! Contributed submissions are due September 16, 2017 5:00:00 AM GMT. That’s less than 6 days away!  We want to make sure we can review submissions early enough to get responses back […]

Self-study resources for Bayes and Stan?

Someone writes: I’m interested in learning more about data analysis techniques; I’ve bought books on Bayesian Statistics (including yours), on R programming, and on several other ‘related stuff’. Since I generally study this whenever I have some free time, I’m looking for sources that are meant for self study. Are there any sources that you […]

Stan Weekly Roundup, 7 September 2017

I was out on vacation last week, but now I’m back! While I was gone… Sean Talts released Stan 2.17 (the math library, the core Stan library, and CmdStan 2.17). RStan and PyStan are in the works. Stan 2.17 will be the last pure C++03 release, that opens up pretty much all of C++11 and […]