This user guide describes a Python package, PyMC, that allows users to efficiently code a probabilistic model and draw samples from its posterior distribution using Markov chain Monte Carlo techniques ...

# MAGIC To import this accelerator, please [clone the repo above into your workspace](https://docs.databricks.com/repos/git-operations-with-repos.html) instead of ...

There are (at least) two packages implementing Monte Carlo sampling available in python: pymc and emcee. pyspeckit includes interfaces to both. With the pymc interface, it is possible to define priors ...

The code is written in Jupyter Notebook format. Data used Data files from the text's support site are cited. The data files are stored in a 'data' folder within the same folder as the Jupyter Notebook ...