PyStan is a Python interface to Stan, a package for Bayesian inference. Stan® is a state-of-the-art platform for statistical modeling and high-performance statistical computation.

The following block of code shows how to use PyStan with a model which studied coaching effects across eight schools (see Section 5.5 of Gelman et al (2003)). This hierarchical model is often called …

Users have reported that PyStan works on several other Linux distributions. If you use an unsupported distribution and find that the PyPI wheels do not work, try installing httpstan from source.

There is one exception: num_chains. num_chains is a PyStan-specific keyword argument. It indicates the number of independent processes to use when drawing samples.

Experience has proven that supporting PyStan on Windows is challenging and requires a considerable investment of resources. If you would like to fund the development and ongoing maintenance of a …

Parameter names are identical to those used in CmdStan. See the CmdStan documentation for parameter descriptions and default values. There is one exception: `num_chains`. `num_chains` is a …

The scope of PyStan 3 is reduced in the interest of freeing up resources to dedicate to making the software more reliable and to guaranteeing timely releases. The default HMC sampler is supported. …

PyStan adopts virtually all the conventions and procedures discussed in Astropy’s How to make a code contribution. In general, contributions which follow the project’s coding style, have tests, and solve a …

[docs] class Fit(collections.abc.Mapping): """Stores draws from one or more chains. Returned by methods of a ``Model``. Users will not instantiate this class directly. A `Fit` instance works like a …

Plugins ¶ This is a guide to installing and creating plugins for PyStan. Installing Plugins ¶ In order to use a plugin, you need to install it. Plugins are published on PyPI and can be installed with pip. Plugins …