[1]
Anderson, P.E. and Smith, J.Q. 2005. A graphical framework for representing the semantics of asymmetric models. University of Warwick, Centre for Research in Statistical Methodology Working papers Vol.2005 (No.12)., (2005).
[2]
Barndorff-Nielsen, O.E. et al. Complex stochastic systems. Chapman & Hall/CRC.
[3]
Berkane, M. Latent variable modeling and applications to causality. Springer.
[4]
Bonet, B. 2001. A Calculus for Causal Relevance. Proceedings of the Seventeen Conference on Uncertainty in Artificial Intelligence (S. Francisco, 2001), 40–47.
[5]
Bonet, B. 2001. Instrumentality Tests Revisited. Proceedings of the Seventeen Conference on Uncertainty in Artificial Intelligence (S. Francisco, 2001), 48–54.
[6]
Capani, A. et al. 2000. CoCoA 4. a system for doing Computations in Commutative Algebra.
[7]
Char, B.W. 1991. Maple V library reference manual. Springer-Verlag.
[8]
Cooper, G.F. and Glymour, C.N. eds. 1999. Computation, causation, and discovery. The MIT Press.
[9]
Cox, D.R. et al. 2001. Complex stochastic systems. Chapman & Hall/CRC.
[10]
Dawid, A.P. 2000. Causal Inference Without Counterfactuals. Journal of the American Statistical Association. 95, 450 (2000), 407–424.
[11]
Dawid, A.P. 2002. Influence Diagrams for Causal Modelling and Inference. International Statistical Review / Revue Internationale de Statistique. 70, 2 (2002), 161–189.
[12]
Gale, W.A. et al. 1986. Artificial intelligence and statistics. Addison-Wesley Pub. Co.
[13]
Mond, D. et al. 2007. Algebraic causality : Bayes nets and beyond. Centre for Research in Statistical Methodology. Working papers, Vol.2007 (No.13)., (2007).
[14]
Monroy, R. and Mexican International Conference on Artificial Intelligence MICAI 2004: advances in artificial intelligence : Third Mexican International Conference on Artificial Intelligence, Mexico City, Mexico, April 26-30, 2004 : proceedings. Springer-Verlag.
[15]
Monroy, R. and Mexican International Conference on Artificial Intelligence MICAI 2004: advances in artificial intelligence : Third Mexican International Conference on Artificial Intelligence, Mexico City, Mexico, April 26-30, 2004 : proceedings. Springer-Verlag.
[16]
Pearl, J. 1995. Causal Diagrams for Empirical Research. Biometrika. 82, 4 (1995), 669–688.
[17]
Pearl, J. 2000. Causality: models, reasoning, and inference. Cambridge University Press.
[18]
Pearl, J. 1993. Comment: Graphical Models, Causality and Intervention. Statistical Science. 8, 3 (1993), 266–269.
[19]
Pearl, J. 2003. Statistics and causal inference: A review. Test. 12, 2 (Dec. 2003), 281–345. DOI:https://doi.org/10.1007/BF02595718.
[20]
Pronzato, L. and Zhigli︠a︡vskiĭ, A.A. 2008. Optimal design and related areas in optimization and statistics. Springer.
[21]
Riccomagno, E. and Smith, J.Q. 2005. The causal manipulation and Bayesian estimation of chain event graphs. (2005).
[22]
Robins, J. 1986. A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect. Mathematical Modelling. 7, 9–12 (1986), 1393–1512. DOI:https://doi.org/10.1016/0270-0255(86)90088-6.
[23]
Shafer, G. 1996. The art of causal conjecture. MIT Press.
[24]
Smith, J.Q. 2010. Bayesian Decision Analysis: Principles and Practice. Cambridge University Press.
[25]
Smith, J.Q. 2010. Bayesian decision analysis: principles and practice. Cambridge University Press.
[26]
Smith, J.Q. and Anderson, P.E. 2008. Conditional independence and chain event graphs. Artificial Intelligence. 172, 1 (Jan. 2008), 42–68. DOI:https://doi.org/10.1016/j.artint.2007.05.004.
[27]
Spirtes, P. et al. 2000. Causation, prediction, and search. MIT Press.
[28]
Spirtes, P. et al. 2000. Causation, prediction, and search. The MIT Press.
[29]
Studený, M. 2005. Probabilistic conditional independence structures. Springer.
[30]
Studený, M. 2005. Probabilistic conditional independence structures. Springer.
[31]
TETRAD 3: Tools for Causal Modeling. User’s Manual: http://www.phil.cmu.edu/tetrad/.
[32]
Thwaites, P.A. and Smith, J.Q. Evaluating Causal effects using Chain Event Graphs. The third Workshop on Probabilistic Graphical Models 291–300.
[33]
2006. Information processing and management of uncertainty knowledge-based systems : proceedings = Traitment d’information et gestion d’incertitudes dans les systemes a base de connaissances : actes : July 2-7, 2006. EDK.
[34]
2004. Proceedings of the 10th Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. Università La Sapienza.