Blog Archives

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

July 15, 2016
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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…

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

July 7, 2016
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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…

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Log Sum of Exponentials for Robust Sums on the Log Scale

June 11, 2016
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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…

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Betancourt Binge (Video Lectures on HMC and Stan)

June 10, 2016
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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…

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A Primer on Bayesian Multilevel Modeling using PyStan

June 9, 2016
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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…

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Beautiful Graphs for Baseball Strike-Count Performance

May 16, 2016
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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…

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

April 14, 2016
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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…

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Stan Case Studies Launches

March 18, 2016
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Stan Case Studies Launches

There’s a new section of the Stan web site, with case studies meant to illustrate statistical methodologies, classes of models, application areas, statistical computation, and Stan programming. Stan Case Studies The first ten or so are up, including a grab bag of education models from Daniel Furr at U.C. Berkeley: Hierarchical Two-Parameter Logistic Item Response […] The post Stan Case Studies Launches appeared first on Statistical Modeling, Causal Inference, and…

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Kéry and Schaub’s Bayesian Population Analysis Translated to Stan

January 21, 2016
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Kéry and Schaub’s Bayesian Population Analysis Translated to Stan

Hiroki ITÔ (pictured) has done everyone a service in translating to Stan the example models [update: only chapters 3–9 so far, not the whole book; the rest are in the works] from Marc Kéry and Michael Schaub (2012) Bayesian Population Analysis using WinBUGS: A Hierarchical Perspective. Academic Press. You can find the code in our […] The post Kéry and Schaub’s Bayesian Population Analysis Translated to Stan appeared first on…

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Jim Albert’s Baseball Blog

January 20, 2016
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Jim Albert’s Baseball Blog

Jim Albert has a baseball blog: Baseball with R I sent a link internally to people I knew were into baseball, to which Andrew replied, “I agree that it’s cool that he doesn’t just talk, he has code.” (No kidding—the latest post as of writing this was on an R package to compute value above […] The post Jim Albert’s Baseball Blog appeared first on Statistical Modeling, Causal Inference, and…

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