Blog Archives

Free workshop on Stan for pharmacometrics (Paris, 22 September 2016); preceded by (non-free) three day course on Stan for pharmacometrics

August 25, 2016
By

So much for one post a day… Workshop: Stan for Pharmacometrics Day If you are interested in a free day of Stan for pharmacometrics in Paris on 22 September 2016, see the registration page: Stan for Pharmacometrics Day (free workshop) Julie Bertrand (statistical pharmacologist from Paris-Diderot and UCL) has finalized the program: When Who What […] The post Free workshop on Stan for pharmacometrics (Paris, 22 September 2016); preceded by…

Read more »

Stan Course up North (Anchorage, Alaska) 23–24 Aug 2016

August 17, 2016
By
Stan Course up North (Anchorage, Alaska) 23–24 Aug 2016

Daniel Lee’s heading up to Anchorage, Alaska to teach a two-day Stan course at the Alaska chapter of the American Statistical Association (ASA) meeting in Anchorage. Here’s the rundown: Information and Free Registration I hear Alaska’s beautiful in the summer—16 hour days in August and high temps of 17 degrees celsius. Plus Stan! More Upcoming […] The post Stan Course up North (Anchorage, Alaska) 23–24 Aug 2016 appeared first on…

Read more »

Stan 2.11 Good, Stan 2.10 Bad

July 31, 2016
By
Stan 2.11 Good, Stan 2.10 Bad

Stan 2.11 is available for all interfaces We are happy to announce that all of the interfaces have been updated to Stan 2.11. There was a subtle bug introduced in 2.10 where a probabilistic acceptance condition was being checked twice. Sorry about that and thanks for your patience. We’ve added some additional tests to catch […] The post Stan 2.11 Good, Stan 2.10 Bad appeared first on Statistical Modeling, Causal…

Read more »

One-day workshop on causal inference (NYC, Sat. 16 July)

July 15, 2016
By

James Savage is teaching a one-day workshop on causal inference this coming Saturday (16 July) in New York using RStanArm. Here’s a link to the details: One-day workshop on causal inference Here’s the course outline: How do prices affect sales? What is the uplift from a marketing decision? By how much will studying for an […] The post One-day workshop on causal inference (NYC, Sat. 16 July) appeared first on…

Read more »

Reproducible Research with Stan, R, knitr, Docker, and Git (with free GitLab hosting)

July 7, 2016
By
Reproducible Research with Stan, R, knitr, Docker, and Git (with free GitLab hosting)

Jon Zelner recently developed a neat Docker packaging of Stan, R, and knitr for fully reproducible research. The first in his series of posts (with links to the next parts) is here: * Reproducibility, part 1 The post on making changes online and auto-updating results using GitLab’s continuous integration service is here: * GitLab continuous […] The post Reproducible Research with Stan, R, knitr, Docker, and Git (with free GitLab…

Read more »

Log Sum of Exponentials for Robust Sums on the Log Scale

June 11, 2016
By

This is a public service announcement in the interest of more robust numerical calculations. Like matrix inverse, exponentiation is bad news. It’s prone to overflow or underflow. Just try this in R: > exp(-800) > exp(800) That’s not rounding error you see. The first one evaluates to zero (underflows) and the second to infinity (overflows). […] The post Log Sum of Exponentials for Robust Sums on the Log Scale appeared…

Read more »

Betancourt Binge (Video Lectures on HMC and Stan)

June 10, 2016
By
Betancourt Binge (Video Lectures on HMC and Stan)

Even better than binging on Netflix, catch up on Michael Betancourt’s updated video lectures, just days after their live theatrical debut in Tokyo. Scalable Bayesian Inference with Hamiltonian Monte Carlo (YouTube, 1 hour) Some Bayesian Modeling Techniques in Stan (YouTube, 1 hour 40 minutes) His previous videos have received very good reviews and they’re only […] The post Betancourt Binge (Video Lectures on HMC and Stan) appeared first on Statistical…

Read more »

A Primer on Bayesian Multilevel Modeling using PyStan

June 9, 2016
By
A Primer on Bayesian Multilevel Modeling using PyStan

Chris Fonnesbeck contributed our first PyStan case study (I wrote the abstract), in the form of a very nice Jupyter notebook. Daniel Lee and I had the pleasure of seeing him present it live as part of a course we were doing at Vanderbilt last week. A Primer on Bayesian Multilevel Modeling using PyStan This […] The post A Primer on Bayesian Multilevel Modeling using PyStan appeared first on Statistical…

Read more »

Beautiful Graphs for Baseball Strike-Count Performance

May 16, 2016
By
Beautiful Graphs for Baseball Strike-Count Performance

This post is by Bob. I have no idea what Andrew will make of these graphs; I’ve been hoping to gather enough comments from him to code up a ggplot theme. Shravan, you can move along, there’s nothing here but baseball. Jim Albert created some great graphs for strike-count performance in a series of two […] The post Beautiful Graphs for Baseball Strike-Count Performance appeared first on Statistical Modeling, Causal…

Read more »

Stan Coding Corner: O(N) Change-Point Program with Clever Forward-Backward Calculation

April 14, 2016
By

It’s so much fun to work in open source. Luke Wiklendt sent along this improved code for a change-point model calculation in Stan. With N data points in the time series, the version in the manual is O(N2), whereas the improved version is O(N). In practice, Luke says [the new code] results in a dramatic […] The post Stan Coding Corner: O(N) Change-Point Program with Clever Forward-Backward Calculation appeared first…

Read more »


Subscribe

Email:

  Subscribe