(This post is by Jonah) Last week I posted here about the release of version 2.0.0 of the loo R package, but there have been a few other recent releases and updates worth mentioning. At the end of the post I also include some general thoughts on R package development with Stan and the growing number of […]

**Stan**

## loo 2.0 is loose

This post is by Jonah and Aki. We’re happy to announce the release of v2.0.0 of the loo R package for efficient approximate leave-one-out cross-validation (and more). For anyone unfamiliar with the package, the original motivation for its development is in our paper: Vehtari, A., Gelman, A., and Gabry, J. (2017). Practical Bayesian model evaluation […]

## StanCon 2018 Live Stream — bad news…. not enough bandwidth

Breaking news: no live stream. We’re recording, so we’ll put the videos online after the fact. We don’t have enough bandwidth to live stream today. StanCon 2018 starts today! We’re going to try our best to live stream the event on YouTube. We have the same video setup as last year, but may […]

## StanCon2018 Early Registration ends Nov 10

StanCon is happening at the beautiful Asilomar conference facility at the beach in Monterey California for three days starting January 10, 2018. We have space for 200 souls and this will sell out. If you don’t already know, Stan is the rising star of probabilistic modeling with Bayesian analysis. If you do statistics, machine learning […]

## 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, […]

## Stan Conference Live Stream

StanCon 2017 is tomorrow! Late registration ends in an hour. After that, all tickets are $400. We’re going to be live streaming the conference. You’ll find the stream as a YouTube Live event from 8:45 am to 6 pm ET (and whatever gets up will be recorded by default). We’re streaming it ourselves, so if there are […]

## StanCon: now accepting registrations and submissions

As we announced here a few weeks ago, the first Stan conference will be Saturday, January 21, 2017 at Columbia University in New York. We are now accepting both conference registrations and submissions. Full details are available at StanCon page on the Stan website. If you have any questions please let us know and we […]

## StanCon is coming! Sat, 1/21/2017

[Update: There’s a more recent post with the schedule.] Save the date! The first Stan conference is going to be in NYC in January. Registration will open at the end of September. When: Saturday, January 21, 2017 9 am – 5 pm Where: Davis Auditorium, Columbia University 530 West 120th Street 4th […]

## NYC Stan meetup 12 December

The next NYC Stan meetup is on Saturday: Feel free to bring things you’re working on or join in on projects some of the others are working on. A couple of the developers will be around to answer questions and help out. If you don’t have anything to work on, the Stan team could use […]

## Daniel on Stan at the NYC Machine Learning Meetup

I (Daniel) will be giving a Stan overview talk on Thursday, August 20, 7 pm. Bob gave a talk there 3.5 years ago. My talk will be light and include where we’ve been and where we’re going. P.S. If you make it, find me. I have Stan stickers to give out. P.P.S. Stan is […]

## ShinyStan v2.0.0

For those of you not familiar with ShinyStan, it is a graphical user interface for exploring Stan models (and more generally MCMC output from any software). For context, here’s the post on this blog first introducing ShinyStan (formerly shinyStan) from earlier this year. ShinyStan v2.0.0 released ShinyStan v2.0.0 is now available on CRAN. This is […]

## Stan is fast

10,000 iterations for 4 chains on the (precompiled) efficiently-parameterized 8-schools model:

## A Stan is Born

Stan 1.0.0 and RStan 1.0.0 It’s official. The Stan Development Team is happy to announce the first stable versions of Stan and RStan. What is (R)Stan? Stan is an open-source package for obtaining Bayesian inference using the No-U-Turn sampler, a variant of Hamiltonian Monte Carlo. It’s sort of like BUGS, but with a different language […]

## Learning Differential Geometry for Hamiltonian Monte Carlo

You can get a taste of Hamiltonian Monte Carlo (HMC) by reading the very gentle introduction in David MacKay’s general text on information theory: MacKay, D. 2003. Information Theory, Inference, and Learning Algorithms. Cambridge University Press. [see Chapter 31, which is relatively standalone and can be downloaded separately.] Follow this up with Radford Neal’s much […]