Conditional Independence, Graphs and d ‐Separation
Timo Koski, John M. Noble · Wiley series in probability and statistics · 2009
This chapter contains sections titled: Joint probabilities Conditional independence Directed acyclic graphs and d-separation The Bayes ball Potentials Bayesian networks Object oriented Bayesian networks d-Separation and conditional independence Markov models and Bayesian networks I-maps and Markov equivalence Notes Exercises: Conditional independence and d-separation