ReddRadar
Agent skill
emcee-mcmc-sampler
emcee MCMC skill for Bayesian parameter estimation and posterior sampling in physics applications
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/science/physics/skills/emcee-mcmc-sampler
Metadata
Additional technical details for this skill
- phase
- 6
- domain
- science
- category
- data-analysis
- specialization
- physics
SKILL.md
emcee MCMC Sampler
Purpose
Provides expert guidance on emcee for Bayesian parameter estimation in physics, including ensemble sampling and convergence diagnostics.
Capabilities
- Affine-invariant ensemble sampling
- Parallel tempering support
- Autocorrelation analysis
- Convergence diagnostics
- Prior/likelihood specification
- Chain visualization
Usage Guidelines
- Model Setup: Define log-probability function
- Initialization: Initialize walkers appropriately
- Sampling: Run ensemble sampler
- Convergence: Check autocorrelation and convergence
- Analysis: Extract posterior distributions
Tools/Libraries
- emcee
- corner
- arviz
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