Pymc Python Packages

causalpy

A Python package for causal inference in quasi-experimental settings

calibr8

Toolbox for non-linear calibration modeling.

actuarcredibility

Credibility models for actuarial pricing: Bühlmann, Bühlmann-Straub, Jewell hierarchical, Hachemeister regression, classical, and Bayesian (PyMC). pip install actuarcredibility

oreum-core

Core tools for use on projects by Oreum Industries

bayesian-pricing

Hierarchical Bayesian models for insurance pricing thin-data segments

pytensor-federated

Distributed differentiable graph computation using PyTensor

insurance-spatial

BYM2 spatial territory ratemaking for insurance pricing — PyMC 5 ICAR, adjacency, Moran's I diagnostics

levy-stable-jax

Lévy's alpha-stable distribution for the Jax numerical framework

simba-mcp

MCP server for SIMBA — connect AI assistants (Claude, Cursor) to Bayesian Marketing Mix Models. Upload data, build models, optimize budgets, and run scenarios through natural language.

bioanchor

🔬 Autonomous Bayesian scientific agent — MCMC analysis, uncertainty quantification, and permanent decentralized archiving. The reproducibility layer for DeSci.

tumoroscope-pymc

'Tumoroscope' model built with PyMC.