stan-bayesian-modeling

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Stan probabilistic programming for Bayesian inference

General

What this skill does


# Stan Bayesian Modeling

## Purpose

Provides Stan probabilistic programming capabilities for Bayesian inference and statistical modeling.

## Capabilities

- Stan model specification
- MCMC sampling (NUTS, HMC)
- Variational inference
- Prior predictive checks
- Posterior predictive checks
- Model comparison (LOO-CV, WAIC)

## Usage Guidelines

1. **Model Specification**: Write Stan code with clear blocks
2. **Prior Selection**: Choose appropriate, weakly informative priors
3. **Diagnostics**: Check Rhat, ESS, and divergences
4. **Model Comparison**: Use LOO-CV for model selection

## Tools/Libraries

- Stan
- CmdStan
- RStan
- PyStan

Files: 1

Size: 0.9 KB

Complexity: 8/100

Category: General

Source: https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/science/mathematics/skills/stan-bayesian-modeling

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