Abstract
AbstractWe clarify and refine the definition of a reciprocal random field on an undirected graph, with the reciprocal chain as a special case, by introducing four new properties: the factorizing, global, local, and pairwise reciprocal properties, in decreasing order of strength, with respect to a set of nodes
$\delta$
. They reduce to the better-known Markov properties if
$\delta$
is the empty set, or, with the exception of the local property, if
$\delta$
is a complete set. Conditions for each reciprocal property to imply the next stronger property are derived, and it is shown that, conditionally on the values at a set of nodes
$\delta_0$
, all four properties are preserved for the subgraph induced by the remaining nodes, with respect to the node set
$\delta\setminus\delta_0$
. We note that many of the above results are new even for reciprocal chains.
Publisher
Cambridge University Press (CUP)
Subject
Statistics, Probability and Uncertainty,General Mathematics,Statistics and Probability
Reference30 articles.
1. Reciprocal processes
2. Processus Gaussiens stationaires réciproques sur un intervalle;Carmichael;C. R. Acad. Sci. Paris Sér. I Math.,1982
3. Gibbs and Markov random systems with constraints
4. Multiinformation and the problem of characterization of conditional independence relations;Studený;Problems Control Inform. Theory,1989