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BridgeStan: Stan model log densities, gradients, Hessians, and transforms in R, Python, and Julia

Bob Carpenter
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We’re happy to announce the official 1.0.0 release of BridgeStan.

What is BridgeStan?

From the documentation:

BridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a Stan model, including log densities, gradients, Hessians, and constraining and unconstraining transforms.

BridgeStan should be useful for developing algorithms and deploying applications. It connects to R and Python through low-level foreign function interfaces (.C and ctypes, respectively) and is thus very performant and portable. It is also easy to install and keep up to date with Stan releases. BridgeStan adds the model-level functionality from RStan/PyStan that is not implemented in CmdStanR/CmdStanPy.

Documentation and source code

Detailed forum post

Here’s a post on the Stan forums with much more detail:

Among other things, it describes the history and relations to other Stan-related projects. Edward Roualdes started the project in order to access Stan models through Julia, then Brian Ward and I (mostly Brian!) helped Edward finish it, with some contributions from Nicholas Siccha.

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