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Conditional Independences among Four Random Variables I*

Published online by Cambridge University Press:  12 September 2008

F. Matúš
Affiliation:
Institute of Information Theory and Automation, Pod vodárenskou věží 4, 182 08 Prague, Czech Republic e-mail: matus@utia.cas.cz, studeny@utia.cas.cz
M. Studený
Affiliation:
Institute of Information Theory and Automation, Pod vodárenskou věží 4, 182 08 Prague, Czech Republic e-mail: matus@utia.cas.cz, studeny@utia.cas.cz

Abstract

The conditional independences within a system of four discrete random variables are studied simultaneously. The problem of where independences can occur at the same time, called the problem of probabilistic representability, is attacked by an analysis of cones of polymatroids. New results on the cone of all polymatroids satisfying Ingleton inequalities imply a substantial reduction of the problem and an explicit description of the remaining open cases.†

Type
Research Article
Copyright
Copyright © Cambridge University Press 1995

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References

[1]Birkhoff, G. (1984) Lattice Theory. Nauka, Moscow. (Russian translation)Google Scholar
[2]Fujishige, S. (1978) Polymatroidal dependence structure of a set of random variables. Infor. Control 39 5572.Google Scholar
[3]Ingleton, A. W. (1971) Conditions for representability and transversality of matroids. Proc. Fr. Br. Conf. Springer-Verlag, LNCS 211, 6267.Google Scholar
[4]Leichtweiss, K. (1980) Konvexe Mengen. VEB Deutscher Verlag der Wissenschaften.Google Scholar
[5]Matúš, F. (1992) Ascending and descending conditional independence relations. Trans. 11th Prague Conf. Infor. Theory, Statistical Decision Functions and Random Processes, Academia, Prague, Vol. B, 181200.Google Scholar
[6]Matúš, F. (1992) On equivalence of Markov properties over undirected graphs. J. Appl. Prob. 29 745749.Google Scholar
[7]Matúš, F. (1994) Probabilistic conditional independence structures and matroid theory: background. Int. J. General Syst. 22 185196.Google Scholar
[8]Matúš, F. (1994) Extreme convex set functions with many nonnegative differences. Discrete Mathematics 135 177191.Google Scholar
[9]Nguyen, H. Q. (1986) Semimodular functions. In: White, N. (ed.), Theory of Matroids, Cambridge University Press.Google Scholar
[10]Pearl, J. (1988) Probabilistic Reasoning in Intelligent Systems. Morgan Kaufman.Google Scholar
[11] Studený, M. (1989) Multiinformation and the problem of characterization of conditional independence relations. Problems of Control and Infor. Theory. 18 316.Google Scholar
[12]Studený, M. (1992) Conditional independence relations have no finite complete characterization. Trans. 11th Prague Conf. on Information Theory. Academia, Prague, Vol. B, 377396.Google Scholar
[13]Studený, M. (1994) Structural semigraphoids. Int. J. General Syst. 22 207217.Google Scholar
[14]Studený, M. (1994) Description of structures of stochastic conditional independence by means of faces and imsets (in three parts). Int. J. General Syst. 23 123137, 207–219, 323–347.Google Scholar
[15]Welsh, D. J. A. (1976) Matroid Theory. Academic Press.Google Scholar