lib-pymc

What problem does it solve?

This Skill empowers users to build, fit, and validate complex Bayesian statistical models, enabling robust probabilistic programming and inference for data analysis.

Core Features & Use Cases

• Bayesian Modeling: Construct hierarchical models, regressions (linear, logistic, Poisson), and time series models.
• Inference Methods: Perform MCMC sampling (NUTS) and variational inference (ADVI).
• Diagnostics & Validation: Assess model convergence, fit, and reliability using ArviZ tools.
• Use Case: Analyze experimental data with uncertainty quantification, build predictive models for scientific research, or perform complex simulations.

Quick Start

Use the lib-pymc skill to build a Bayesian linear regression model for the provided data.