Gibbs sampling is a Markov Chain Monte Carlo (MCMC) algorithm used for generating samples from the joint distribution of a set of random variables, especially when direct sampling is complex or infeasible. It is particularly popular in Bayesian statistics, where it's used to perform posterior inference. ### Key Concepts of Gibbs Sampling: 1. **Goal**: The main purpose of Gibbs sampling is to approximate the joint distribution of multiple variables.

Ancestors (6)

  1. Statistical mechanics
  2. Applied probability
  3. Applied mathematics
  4. Fields of mathematics
  5. Mathematics
  6. Home

View article source

Discussion (0)

New discussion

There are no discussions about this article yet.

Articles by others on the same topic (0)

There are currently no matching articles.
See all articles in the same topic Create my own version