Hamiltonian Monte Carlo For Dummies (Statisticians / Pharmacometricians / All)
Hamiltonian Monte Carlo (HMC) is the best MCMC method for complex, high dimensional, Bayesian modelling. This tutorial aims to provide an introduction to HMC through worked examples ranging from elementary to complex models.
▶︎
The intuition behind the Hamiltonian Monte Carlo algorithm
▶︎
Michael Betancourt: Scalable Bayesian Inference with Hamiltonian Monte Carlo
▶︎
6. Monte Carlo Simulation
▶︎
Hamiltonian Monte Carlo and Stan -- Michael Betancourt (Part 2)
▶︎
17. Bayesian Statistics
▶︎
Markov chain Monte Carlo
▶︎
The better way to do statistics | Bayesian #1
▶︎
Markov Chain Monte Carlo Explained in 10 Minutes
▶︎
Sequential Monte Carlo samplers 1; context
▶︎
A Beginner's Guide to Monte Carlo Markov Chain MCMC Analysis 2016
▶︎
Chris Fonnesbeck: An introduction to Markov Chain Monte Carlo using PyMC3 | PyData London 2019
▶︎
What the Armor of God Really Means When You Feel Too Weak to Fight (No Ads)
▶︎
Introduction to Bayesian data analysis - part 1: What is Bayes?
▶︎
Hamiltonian Monte Carlo
▶︎
Peadar Coyle - A modern introduction to Hamiltonian Monte Carlo and Bayesian workflows
▶︎
The Strange Math That Predicts (Almost) Anything
▶︎
Scalable Bayesian Inference with Hamiltonian Monte Carlo
▶︎
11e Machine Learning: Markov Chain Monte Carlo
▶︎
Introduction to Bayesian statistics, part 2: MCMC and the Metropolis–Hastings algorithm
▶︎