The wikipage of Bayesian Network says
"Formally, Bayesian networks are directed acyclic graphs whose nodes represent random variables in the Bayesian sense"
But in the model I need to build, cyclic structure of constraint is necessary. For example, A influences B, B influences C, C influences A.
What should I use then(instead of Bayesian Network)?
ps. I saw "Markov Network", but it says that the variables should have the "Markov property"(Memorylessness), which is not necessarily true in my intended application, in the sense that some variable is influenced by the history of others as well as its own.
Thank You!
Matt