Contents

pymc 5.17.0

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Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with PyTen

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with PyTensor

Stars: 8674, Watchers: 8674, Forks: 2004, Open Issues: 303

The pymc-devs/pymc repo was created 15 years ago and the last code push was Yesterday.
The project is extremely popular with a mindblowing 8674 github stars!

How to Install pymc

You can install pymc using pip

pip install pymc

or add it to a project with poetry

poetry add pymc

Package Details

Author
None
License
Apache License, Version 2.0
Homepage
http://github.com/pymc-devs/pymc
PyPi:
https://pypi.org/project/pymc/
GitHub Repo:
https://github.com/pymc-devs/pymc

Classifiers

  • Scientific/Engineering
  • Scientific/Engineering/Mathematics
No  pymc  pypi packages just yet.

Errors

A list of common pymc errors.

Code Examples

Here are some pymc code examples and snippets.

GitHub Issues

The pymc package has 303 open issues on GitHub

  • BUG: failed to import pymc on macOS ventura 13.4 using conda env
  • ⬆️ UPGRADE: Autoupdate pre-commit config
  • Don't force upcast to float64 in Simplex transform
  • BUG: Dirichlet is not tolerant to floatX=float32
  • Implement logprob derivation for Max and Min
  • Logprob derivation for Max
  • Add icdf functions for Lognormal, Half Cauchy and Half Normal distributions
  • Remove some math utilities from the PyMC root scope?
  • Passing dims=(dim1, dim2) in gp.prior leads to shape inconcistency
  • Numpyro sampler nuts_kwargs can't be passed from sample
  • Adding meta-information for MeasurableOps
  • BUG: Mac install issue
  • Use numpy testing utilities instead of custom close_to*
  • Wrap sigma parameter with as_tensor_variable() before get_tau_sigma()
  • BUG: Jax-based samplers crash at transformation stage

See more issues on GitHub

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pyflux is a Python library designed for time series analysis. It includes modern time series models, including ARIMA, GARCH, and state space models. With a flexible set of inference options, pyflux enables a probabilistic approach to time series modeling. Though still in alpha, it's an invaluable tool for statisticians and data scientists working with time series data.