In this paper we have solved the open problem of generating random vectors when the underlying structure obeyed by the dependence graph is a Directed Acyclic Graph (DAG). To the best of our knowledge, our work is of a pioneering sort. We present a formal strategy for the case when the DAG structure and the marginals are given. The paper presents the formal algorithm, proves its correctness, derives its complexity, and presents examples for both artificial data, and for data that is intended to artificially populate a medical database [8]. The method has also been used for testing the ALARM network [1].

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Conference 2002 IEEE International Conference on Systems, Man and Cybernetics
Citation
Ouerd, M. (M.), Oommen, J, & Matwin, S. (S.). (2002). Data generation for testing DAG-structured Bayesian networks. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (pp. 278–283).