PyMC Bayesian Modeler Purpose Provides expert guidance on PyMC for Bayesian modeling in physics, including hierarchical models and advanced inference methods. Capabilities - Probabilistic model construction - NUTS/HMC sampling - Variational inference - Gaussian processes - Model comparison (WAIC, LOO) - Prior predictive checks Usage Guidelines 1. Model Building : Construct probabilistic models 2. Priors : Specify informative or weakly informative priors 3. Sampling : Use NUTS for efficient sampling 4. Diagnostics : Check convergence with trace plots and r-hat 5. Comparison : Compare models wi…