[1] S. A. Andersson, D. Madigan, and M. D. Perlman:
An alternative Markov property for chain graphs. In: Uncertainty in Artificial Intelligence, Proc. Twelfth Conference (F. Jensen and E. Horvitz, eds.), Morgan Kaufmann, San Francisco 1996, pp. 40–48.
MR 1617123
[2] S. A. Andersson, D. Madigan, and M. D. Perlman:
A characterization of Markov equivalence classes for acyclic digraphs. Ann. Statist. 25 (1997), 505–541.
MR 1439312
[3] S. A. Andersson, D. Madigan, and M. D. Perlman:
On the Markov equivalence of chain graphs, undirected graphs and acyclic digraphs. Scand. J. Statist. 24 (1997), 81–102.
MR 1436624
[4] S. A. Andersson, D. Madigan, and M. D. Perlman:
Alternative Markov properties for chain graphs. Scand. J. Statist. 28 (2001), 33–85.
MR 1844349
[5] D. M. Chickering:
A transformational characterization of equivalent Bayesian network structures. In: Uncertainty in Artificial Intelligence, Proc. Eleventh Conference (P. Besnard and S. Hanks, eds.), Morgan Kaufmann, San Francisco 1995, pp. 87–98.
MR 1615012
[7] S. L. Lauritzen and N. Wermuth: Mixed Interaction Models. Research Report No. R-84-8, Inst. Elec. Sys., University of Aalborg 1984.
[8] S. L. Lauritzen and N. Wermuth:
Graphical models for association between variables, some of which are qualitative and some quantitative. Ann. Statist. 17 (1989), 31–57.
MR 0981437
[10] J. Pearl:
Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann, San Mateo 1988.
MR 0965765 |
Zbl 0746.68089
[11] A. Roverato:
A unified approach to the characterisation of equivalence classes of DAGs, chain graphs with no flags and chain graphs. Scand. J. Statist. 32 (2005), 295–312.
MR 2188675
[12] A. Roverato and M. Studený:
A graphical representation of equivalence classes of AMP chain graphs. J. Machine Learning Research 7 (2006), 1045–1078.
MR 2274397
[13] Š. Štěpánová: Equivalence of Chain Graphs (in Czech). Diploma Thesis, Charles University, Prague 2003.
[14] M. Studený:
A recovery algorithm for chain graphs. Internat. J. Approx. Reasoning 17 (1997), 265–293.
MR 1462716
[15] M. Studený:
Characterization of essential graphs by means of the operation of legal merging of components. Internat. J. Uncertainty, Fuzziness and Knowledge-Based Systems 12 (2004), 43–62.
MR 2058946
[16] M. Studený and J. Vomlel: Transition between graphical and algebraic representatives of Bayesian network models. In: Proc. 2nd European Workshop on Probabilistic Graphical Models (P. Lucas ed.), Leiden 2004, pp. 193–200.
[17] M. Studený: Probabilistic Conditional Independence Structures. Springer-Verlag, London 2005.
[18] T. Verma and J. Pearl: Equivalence and synthesis of causal models. In: Uncertainty in Artificial Intelligence, Proc. Sixth Conference (P. Bonissone, M. Henrion, L. N. Kanal, and J. F. Lemmer, eds.), North-Holland, Amsterdam 1991, pp. 255–270.
[19] M. Volf and M. Studený:
A graphical characterization of the largest chain graphs. Internat. J. Approx. Reasoning 20 (1999), 209–236.
MR 1685080