This article is a Python copying activity record of Chapter 9, Part 3: 'Logistic Regression Model' from the book 'Introduction to Data Analysis with Bayesian Statistical Modeling using R and Stan'.
These steps install everything at the user level so the agents, skills, and settings are available across all your projects (Claude Code reads from ~/.claude/ on ...
Libraries for building AI applications, LLM integrations, and autonomous agents.
PyMC : a modern, and comprehensive probabilistic programming framework in Python Oriol Abril-Pla, Virgile Andreani, Colin Carroll, Larry Dong, Christopher J. Fonnesbeck, Maxim Kochurov, Ravin Kumar, ...
26 ]. We used PyMC v5.0 for all analyses [ 27 ]. 3.3.3 Posterior predictive checks We evaluated model fit by comparing observed outcomes to posterior predictive distributions, using chi-square ...
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