Stan is software for Bayesian estimation using the No-U-Turn sampling (NUTS) algorithm instead of the simpler Gibbs sampling (BUGS).
Stan is software for Bayesian estimation using the No-U-Turn sampling (NUTS) algorithm instead of the simpler Gibbs sampling (BUGS). It is specially useful for models that have highly correlated posterior distributions and thus where the Gibbs sampler would take too long to converge.
It also implements algorithms such as BFGS to solve optimization problems.
Stan is open-source. It can be used as stand-alone software, or can interface with either R (via RStan) or Python (via PyStan).
To understand the contrast between the MCMC sampling algorithms, see:
- Can someone explain Gibbs sampling in very simple words? (A very helpful CV thread.)
- Hoffman, M.D. & Gelman, A. (2011). The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo. http://arxiv.org/abs/1111.4246v1
