I'm been trying to understand Gibbs sampling.

What I'm looking for is a paper or other reference which uses a simple canonical example and uses that to illustrate Gibbs sampling.

Sadly I've not found one that does that.

Would appreciate any such reference or other advice.


  • $\begingroup$ You should probably state which papers (etc) you've looked at and in what ways they were inadequate $\endgroup$
    – Glen_b
    Jul 6, 2015 at 6:27
  • $\begingroup$ You may want to wait to see if you get better answers; you should feel free to move the tick if you do. $\endgroup$
    – Glen_b
    Jul 6, 2015 at 7:11

2 Answers 2


Some suggestions:

Casella, G. & George, E.I. (1992),
"Explaining the Gibbs Sampler,"
The American Statistician, 46(3) (Aug.), pp. 167-174

chatty with very simple examples, but to me didn't quite motivate as well as:

Gelfand, A.E., & Smith, A.F.M. (1990),
"Sampling-Based Approaches to Calculating Marginal Densities,"
Journal of the American Statistical Association, 85, 398-409.

which has a slightly more theoretical approach. The immediately following paper in the same issue of the journal has some good real data examples.


Andrieu, C. et al. (2003) "An Introduction to MCMC for Machine Learning"

which covers Gibbs sampling in section 3.4, though I'd encourage you to read from the beginning. I liked it because it puts the subject well in perspective and was quite accessible to me.


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