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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.

Thanks.

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  • $\begingroup$ 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

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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.

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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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