bayesian-inference-engine

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Bayesian probabilistic reasoning for prior specification, posterior computation, and belief updating

General

What this skill does


# Bayesian Inference Engine

## Purpose

Provides Bayesian probabilistic reasoning capabilities for prior specification, posterior computation, and sequential belief updating.

## Capabilities

- Prior elicitation support
- MCMC sampling (NUTS, HMC)
- Variational inference
- Model comparison (Bayes factors, LOO-CV)
- Posterior predictive checking
- Sequential belief updating

## Usage Guidelines

1. **Prior Selection**: Choose appropriate, defensible priors
2. **Sampling**: Use efficient MCMC algorithms
3. **Diagnostics**: Check convergence and mixing
4. **Model Comparison**: Use appropriate comparison criteria

## Tools/Libraries

- PyMC
- Stan (PyStan)
- ArviZ
- NumPyro

Files: 1

Size: 1.0 KB

Complexity: 8/100

Category: General

Source: https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/science/scientific-discovery/skills/bayesian-inference-engine

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