 Bayesian inference using Gibbs sampling

Bayesian inference using Gibbs sampling is a statistical technique used to estimate the posterior distribution of parameters in a Bayesian model. This approach is particularly useful when the posterior distribution is complex and difficult to sample from directly. Here's a breakdown of the components involved: ### Bayesian Inference Bayesian inference is based on Bayes' theorem, which updates the probability estimate for a hypothesis as additional evidence is available.