One is an accident. Two is a coincidence. Three is a pattern.
Perhaps it’s no coincidence that there are three new interfaces that use Stan’s C++ implementation of adaptive Hamiltonian Monte Carlo (currently an updated version of the no-U-turn sampler).
- ScalaStan embeds a Stan-like language in Scala. It’s a Scala package largely (if not entirely written by Joe Wingbermuehle.
- tmbstan lets you fit TMB models with Stan. It’s an R package listing Kasper Kristensen as author.
- SlicStan is a “blockless” and self-optimizing version of Stan. It’s a standalone language coded in F# written by Maria Gorinova.
[pdf language spec]
These are in contrast with systems that entirely reimplement a version of the no-U-turn sampler, such as PyMC3, ADMB, and NONMEM.