Stan is freedom-respecting, open-source software for facilitating statistical inference at the frontiers of applied statistics.
Or to put it another way, it makes Bayesian inference fast and (a bit) easier.
StanCon is the premier conference for all things Stan related and this year it will take place at the Asilomar Conference Grounds, a National Historic Landmark on the Monterey Peninsula right on the beach.
RStan and other interfaces
One of the great features about Stan is that you can use Stan via R (or Python or …). The {rstan} package can be in installed in the usual way
install.packages("rstan")
and has been around for a few years, so is fairly stable. The easiest way to get started is to check out the rstan wiki page, which gives a couple of worked through examples.
Training
If you are interested in learning more about Stan, we run a two-day introduction to stan course. The course covers
- Introduction to Bayesian inference: A brief overview of the main ideas behind Bayesian inference.
- Markov chain Monte Carlo methods: A brief overview of Markov chain Monte Carlo methods for Bayesian computation and Hamiltonian Monte Carlo.
- The Stan language: An outline of the main components of a Stan program.
- Using RStan: A guide to the use of the R interface to Stan.
- Examples: Including linear regression, Poisson regression and hierarchical models
Space is limited.
