AI & Machine Learning
AlterLab PyMC
Bayesian modeling and probabilistic programming with PyMC 6 and ArviZ 1.x — hierarchical models, MCMC (NUTS via PyMC, nutpie, NumPyro, or BlackJAX), variational inference, PSIS-LOO model comparison, and prior/posterior predictive checks. Use when fitting Bayesian or hierarchical models, estimating posteriors and credible intervals, diagnosing divergences, R-hat, or ESS, running probabilistic inference, or comparing models with LOO (WAIC was removed from ArviZ 1.x). Part of the AlterLab Academic Skills suite.
- Publisher / source
- AlterLab-IEU/AlterLab-Academic-Skills (found on the CSV list)
- Upstream record
- AlterLab-IEU/AlterLab-Academic-Skills
- Version
- Version 2
- Published
- Publication review
- Approved for publication
- Content fingerprint
81b011537c8bfeddd924861949dc25be714a3421cfa4949d605bb8a0bc14a455