Centered versus non-centered hierarchical models

What are divergent iterations and what to do about them?

How to code up a model with discrete parameters in Stan

Lesson 22a Hierarchical Bayes: Concepts

Explaining the difference between confidence and credible intervals

The intuition behind the Hamiltonian Monte Carlo algorithm

The problems with using simple Monte Carlo to determine the marginal likelihood

1. Algorithms and Computation

Bayesian Hierarchical Models

Why do we need MCMC and how does it work? -- Ben Lambert (Oxford)

How to write your first Stan program

How to code up a bespoke probability density in Stan

Constrained parameters? Use Metropolis-Hastings

Introducing Bayes factors and marginal likelihoods

Tech talk: A practical introduction to Bayesian hierarchical modelling

An introduction to Gibbs sampling

How to derive a Gibbs sampling routine in general

Lecture 18 - Hierarchical Bayesian Models

What is a posterior predictive check and why is it useful?

Hanna van der Vlis - Clusterf*ck: A Practical Guide to Bayesian Hierarchical Modeling in PyMC3

An introduction to importance sampling