Programming a Gibbs sampler

⭐ Purpose

This code consists of a programming exercise that I worked on in the first semester of my M.Sc. studies in Methodology and Statistics at the University of Utrecht. I manually compute a Gibbs sampler to construct posterior distributions in linear regression models.

Specifically, I

• compute the OLS solution using linear algebra to derive starting values for sampling
• run two separate MCMC chains sampling from the conditional posterior distribution of each parameter
• construct measures for autocorrelation and convergence

💎 How can you use it?

This exercise was primary a programming task as part of my studies. However, it did come in handy for me when I needed a quick Gibbs sampler for Bayesian inference that does not need any Stan compilation.