Sampling decomposable graphs using a Markov chain on junction trees

  title={Sampling decomposable graphs using a Markov chain on junction trees},
  author={Peter J. Green},
This paper makes two contributions to the computational geometry of decomposable graphs, aimed primarily at facilitating statistical inference about such graphs where they arise as assumed conditional independence structures in stochastic models. The first of these provides sufficient conditions under which it is possible to completely connect two disconnected cliques of vertices, or perform the reverse procedure, yet maintain decomposability of the graph. The second is a new Markov chain Monte… CONTINUE READING
15 Citations
12 References
Similar Papers


Publications referenced by this paper.
Showing 1-10 of 12 references

Decomposable graphical Gaussian model determination

  • P. Giudici, P. J. Green
  • Biometrika, 86, 785–801.
  • 1999
Highly Influential
6 Excerpts

Decomposition of maximum likelihood in mixed interaction models

  • M. Frydenberg, S. L. Lauritzen
  • Biometrika, 76, 539–55.
  • 1989
Highly Influential
4 Excerpts

A theorem on trees

  • A. Cayley
  • Quarterly Journal of Mathematics, 23, 376–8.
  • 1889
Highly Influential
3 Excerpts

Graphical Models

  • S. L. Lauritzen
  • Clarendon Press, Oxford.
  • 1996
2 Excerpts

Similar Papers

Loading similar papers…