Category: Stan

A heart full of hatred: 8 schools edition

No; I was all horns and thorns Sprung out fully formed, knock-kneed and upright — Joanna Newsom Far be it for me to be accused of liking things. Let me, instead, present a corner of my hateful heart. (That is to say that I’m supposed to be doing a really complicated thing right now and […]

Stan contract jobs!

Sean writes: We are starting to get money and time to manage paid contracting jobs to try to get a handle on some of our technical debt. Any or all of the skills could be valuable: C++ software engineering C++ build tools, compilers, and toolchains Creating installers or packages of any kind (especially cross-platform) Windows […]

Golf example now a Stan case study!

It’s here! (and here’s the page with all the Stan case studies). In this case study, I’m following up on two earlier posts, here and here, which in turn follow up this 2002 paper with Deb Nolan. My Stan case study is an adaptation of a model fit by Columbia business school professor and golf […]

don’t be late for BayesComp’2020

An important reminder that October 14 is the deadline for regular registration to BayesComp 2020 as late fees will apply afterwards!!! The conference looks attractive enough to agree to pay more, but still…

Convergence diagnostics for Markov chain simulation

Pierre Jacob writes regarding convergence diagnostics for Markov chain simulation: I’ve implemented an example of TV upper bounds for (vanilla) HMC on a model written in Stan, see here and here for a self-contained R script. Basically, this creates a stan fit object to obtain a target’s pdf and gradient, and then implements a pure […]

Seeking postdoc (or contractor) for next generation Stan language research and development

The Stan group at Columbia is looking to hire a postdoc* to work on the next generation compiler for the Stan open-source probabilistic programming language. Ideally, a candidate will bring language development experience and also have research interests in a related field such as programming languages, applied statistics, numerical analysis, or statistical computation. The language […]

deadlines for BayesComp’2020

While I have forgotten to send a reminder that August 15 was the first deadline of BayesComp 2020 for the early registrations, here are further deadlines and dates BayesComp 2020 occurs on January 7-10 2020 in Gainesville, Florida, USA Registration is open with regular rates till October 14, 2019 Deadline for submission of poster proposals […]

Why does my academic lab keep growing?

Andrew, Breck, and I are struggling with the Stan group funding at Columbia just like most small groups in academia. The short story is that to apply for enough grants to give us a decent chance of making payroll in the following year, we have to apply for so many that our expected amount of […]

The Economist does Mister P

Elliott Morris points us to this magazine article, “If everyone had voted, Hillary Clinton would probably be president,” which reports: Close observers of America know that the rules of its democracy often favour Republicans. But the party’s biggest advantage may be one that is rarely discussed: turnout is just 60%, low for a rich country. […]

Software release strategies

Scheduled release strategy Stan’s moved to a scheduled release strategy where we’ll simply release whatever we have every three months. The Stan 2.20 release just went out last week. So you can expect Stan 2.21 in three months. Our core releases include the math library, the language compiler, and CmdStan. That requires us to keep […]

ateliers statistiques bayésiens

The French Statistical Association is running a training workshop on practical computational Bayesian methods on 10-12 September 2019 in Paris (IHP), animated by Sylvain LE CORFF (Telecom SudParis – Institut Polytechnique de Paris) for the initia…

Healthier kids: Using Stan to get more information out of pediatric respiratory data

Robert Mahar, John Carlin, Sarath Ranganathan, Anne-Louise Ponsonby, Peter Vuillermin, and Damjan Vukcevic write: Paediatric respiratory researchers have widely adopted the multiple-breath washout (MBW) test because it allows assessment of lung function in unsedated infants and is well suited to longitudinal studies of lung development and disease. However, a substantial proportion of MBW tests in […]

They’re looking to hire someone with good working knowledge of Bayesian inference algorithms development for multilevel statistical models and mathematical modeling of physiological systems.

Frederic Bois writes: We have an immediate opening for a highly motivated research / senior scientist with good working knowledge of Bayesian inference algorithms development for multilevel statistical models and mathematical modelling of physiological systems. The successful candidate will assist with the development of deterministic or stochastic methods and algorithms applicable to systems pharmacology/biology models […]

Read this: it’s about importance sampling!

Importance sampling plays an odd role in statistical computing. It’s an old-fashioned idea and can behave just horribly if applied straight-up—but it keeps arising in different statistics problems. Aki came up with Pareto-smoothed importance sampling (PSIS) for leave-one-out cross-validation. We recently revised the PSIS article and Dan Simpson wrote a useful blog post about it […]

How does Stan work? A reading list.

Bob writes, to someone who is doing work on the Stan language: The basic execution structure of Stan is in the JSS paper (by Bob Carpenter, Andrew Matt Hoffman, Daniel Lee, Ben Goodrich, Michael Betancourt, Marcus Brubaker, Jiqiang Guo, Peter Li, and Allen Riddell) and in the reference manual. The details of autodiff are in […]

AnnoNLP conference on data coding for natural language processing

This workshop should be really interesting: Aggregating and analysing crowdsourced annotations for NLP EMNLP Workshop. November 3–4, 2019. Hong Kong. Silviu Paun and Dirk Hovy are co-organizing it. They’re very organized and know this area as well as anyone. I’m on the program committee, but won’t be able to attend. I really like the problem […]

Question 3 of our Applied Regression final exam (and solution to question 2)

Here’s question 3 of our exam: Here is a fitted model from the Bangladesh analysis predicting whether a person with high-arsenic drinking water will switch wells, given the arsenic level in their existing well and the distance to the nearest safe well. glm(formula = switch ~ dist100 + arsenic, family=binomial(link=”logit”)) coef.est coef.se (Intercept) 0.00 0.08 […]