---
name: pymc-probabilistic-programming-6466801968cb
description: PyMC for flexible Bayesian modeling
allowed-tools:
  - Bash
  - Read
  - Write
  - Edit
  - Glob
  - Grep
metadata:
  specialization: mathematics
  domain: science
  category: statistical-computing
  phase: 6
graph:
  domains: [domain:mathematics]
  specializations: [specialization:computational-mathematics]
  skillAreas: [skill-area:statistical-analysis, skill-area:mathematical-reasoning, skill-area:data-analysis]
  workflows: [workflow:experiment-design]
  roles: [role:research-scientist, role:data-scientist]
---

# PyMC Probabilistic Programming

## Purpose

Provides PyMC capabilities for flexible Bayesian modeling and probabilistic programming in Python.

## Capabilities

- Hierarchical model specification
- Custom distributions
- Gaussian processes
- MCMC and variational inference
- Model diagnostics
- ArviZ integration for visualization

## Usage Guidelines

1. **Model Building**: Use PyMC context managers
2. **Custom Distributions**: Define distributions when needed
3. **Hierarchical Models**: Build proper hierarchical structures
4. **Visualization**: Use ArviZ for diagnostic plots

## Tools/Libraries

- PyMC
- ArviZ
- Theano/PyTensor


---
Source attribution: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Data & Analytics, Development & Engineering, Education & Research, Product Management
Roles: Data Analyst, Data Scientist, ML / AI Engineer, Product Manager, Researcher
Specialties: API
Tools: Arviz, Pymc, Theano/Pytensor
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 9666b374f64ff38efa39736fa90d719d2c5e7d354bd1f3be247612327322478c