# Gibbs sampling as a special case of Metropolis-Hastings

## Summary

Gibbs sampling can be seen as a special case of the Metropolis-Hastings algorithm where the transition operators are chosen such that the acceptance probability is 1.

## Context

This concept has the prerequisites:

## Core resources (we're sorry, we haven't finished tracking down resources for this concept yet)

## Supplemental resources (the following are optional, but you may find them useful)

## -Paid-

→ Pattern Recognition and Machine Learning

A textbook for a graduate machine learning course, with a focus on Bayesian methods.

Location:
page 544 of section 11.3

→ Machine Learning: a Probabilistic Perspective

A very comprehensive graudate-level machine learning textbook.

Location:
section 24.3.2, pages 849-850

## See also

-No Additional Notes-