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Mcmc diagnostics

Skill a5c-ai/babysitter/library/specializations/domains/science/mathematics/skills/mcmc-diagnostics

MCMC convergence diagnostics and analysisFrom its SKILL.md

Install
npx -y skills add a5c-ai/babysitter --skill mcmc-diagnostics

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

1.2 KB, 158 tokens by cl100k_base, as published. Nobody here has run it

MCMC Diagnostics

Purpose

Provides MCMC convergence diagnostics and analysis capabilities for validating Bayesian inference results.

Capabilities

  • Rhat (potential scale reduction) computation
  • Effective sample size (ESS) calculation
  • Trace plot generation
  • Autocorrelation analysis
  • Divergence detection
  • Energy diagnostic (E-BFMI)

Usage Guidelines

  1. Convergence Check: Verify Rhat < 1.01 for all parameters
  2. Sample Quality: Ensure ESS is sufficient for inference
  3. Visual Inspection: Review trace plots for mixing
  4. Divergences: Address divergent transitions

Tools/Libraries

  • ArviZ
  • CODA
  • MCMCpack

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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