Bayesian Inference

concepts · 18 notes linked

Related: Markov Chain Monte Carlo · Probabilistic Programming · Pymc · Hierarchical Models · Pymc3 · Probabilistic Modeling · Conjugate Prior · Prior Probability

Notes

• A Primer on Bayesian Methods for Multilevel Modeling — Bayesian hierarchical modeling with PyMC3 using partial pooling
• Bayes' Rule Goes Quantum: A 250-Year-Old Theory Learns New Tricks — Quantum Bayes' rule derived from minimum-change principle matches Petz recovery map
• Beta distribution - Wikipedia — Continuous distribution on [0,1] conjugate prior for Bernoulli/binomial
• Cromwell's rule - Wikipedia — Bayesian principle against assigning zero or one prior probability to hypotheses
• De Finetti's theorem - Wikipedia — Exchangeable observations are conditionally independent given latent variable
• Dirichlet distribution - Wikipedia — Multivariate continuous distribution over probability simplices used as Bayesian prior
• GitHub - CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers: aka \"Bayesian Methods for Hackers\ — Open-source computation-first Bayesian inference book using PyMC
• Interpreting Covid-19 Test Results: A Bayesian Approach — Bayesian pretest-probability framework for interpreting COVID-19 test results
• Kullback-Leibler divergence - Wikipedia — Asymmetric measure of difference between two probability distributions
• Markov Chain Monte Carlo in Python | Towards Data Science — Complete real-world MCMC implementation using PyMC3 on sleep data
• Markov Models of Social Change (Part 1) — Cross-impact balance analysis with stochastic succession rules for social scenarios
• Probabilistic Modeling and Statistical Inference — Bayesian and frequentist foundations for principled statistical inference
• Rule of succession - Wikipedia — Laplace's formula estimating next-trial success probability from observed counts
• Statistics for Hackers — Replacing classical statistics jargon with computational simulation approaches
• The Stan Forums — Community Q&A forum for the Stan probabilistic programming language
• Using PyMC3 — Hands-on PyMC3 tutorial covering MCMC samplers and Bayesian models
• WebPPL — JavaScript-embedded probabilistic programming language for Bayesian modeling
• – while my_mcmc: gently(samples) — Thomas Wiecki's Bayesian/MCMC personal blog and AI reflection posts