1.
Anderson PE, Smith JQ. A graphical framework for representing the semantics of asymmetric models. 2005;University of Warwick, Centre for Research in Statistical Methodology Working papers Vol.2005 (No.12). http://wrap.warwick.ac.uk/35587/
2.
Bonet B. A Calculus for Causal Relevance. In: Proceedings of the Seventeen Conference on Uncertainty in Artificial Intelligence. Morgan Kaufmann; 2001:40-47. http://arxiv.org/abs/1301.2257?
3.
Bonet B. Instrumentality Tests Revisited. In: Proceedings of the Seventeen Conference on Uncertainty in Artificial Intelligence. Morgan Kaufmann Publishers; 2001:48-54. http://arxiv.org/abs/1301.2258?
4.
Capani A, Niesi G, Robbiano L. CoCoA 4. a system for doing Computations in Commutative Algebra. Published online 2000. http://cocoa.dima.unige.it
5.
Char BW. Maple V Library Reference Manual. Springer-Verlag; 1991.
6.
Gale WA, AT & T Bell Laboratories, Workshop on Artificial Intelligence and Statistics. Artificial Intelligence and Statistics. Addison-Wesley Pub. Co; 1986.
7.
Dawid AP. Causal Inference Without Counterfactuals. Journal of the American Statistical Association. 2000;95(450):407-424. http://0-www.jstor.org.pugwash.lib.warwick.ac.uk/stable/2669377
8.
Dawid AP. Influence Diagrams for Causal Modelling and Inference. International Statistical Review / Revue Internationale de Statistique. 2002;70(2):161-189. http://0-www.jstor.org.pugwash.lib.warwick.ac.uk/stable/1403901
9.
Cooper GF, Glymour CN, eds. Computation, Causation, and Discovery. The MIT Press; 1999. http://0-cognet.mit.edu.pugwash.lib.warwick.ac.uk/book/computation-causation-and-discovery
10.
Barndorff-Nielsen OE, Cox DR, Klüppelberg C. Complex Stochastic Systems. Vol Monographs on statistics and applied probability. Chapman & Hall/CRC http://0-marc.crcnetbase.com.pugwash.lib.warwick.ac.uk/isbn/9781420035988
11.
Cox DR, Klüppelberg C, Barndorff-Nielsen OE. Complex Stochastic Systems. Vol Monographs on statistics and applied probability. Chapman & Hall/CRC; 2001.
12.
Monroy R, 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. Vol 2972. Springer-Verlag https://0-link-springer-com.pugwash.lib.warwick.ac.uk/10.1007/b96521
13.
Monroy R, 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. Vol 2972. Springer-Verlag https://0-link-springer-com.pugwash.lib.warwick.ac.uk/10.1007/b96521
14.
Mond D, Riccomagno E, Smith JQ. Algebraic causality : Bayes nets and beyond. 2007;Centre for Research in Statistical Methodology. Working papers, Vol.2007 (No.13). http://wrap.warwick.ac.uk/35544
15.
Pearl J. Comment: Graphical Models, Causality and Intervention. Statistical Science. 1993;8(3):266-269. http://0-www.jstor.org.pugwash.lib.warwick.ac.uk/stable/2245965
16.
Pearl J. Causal Diagrams for Empirical Research. Biometrika. 1995;82(4):669-688. http://0-www.jstor.org.pugwash.lib.warwick.ac.uk/stable/2337329
17.
Pearl J. Causality: Models, Reasoning, and Inference. Cambridge University Press; 2000.
18.
Proceedings of the 10th Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. Università La Sapienza; 2004.
19.
Riccomagno E, Smith JQ. The causal manipulation and Bayesian estimation of chain event graphs. Published online 2005. http://wrap.warwick.ac.uk/35590/
20.
Pronzato L, Zhigli︠a︡vskiĭ AA. Optimal Design and Related Areas in Optimization and Statistics. Vol Springer optimization and its applications. Springer; 2008. http://0-link.springer.com.pugwash.lib.warwick.ac.uk/chapter/10.1007%2F978-0-387-79936-0_6
21.
Pearl J. Statistics and causal inference: A review. Test. 2003;12(2):281-345. doi:10.1007/BF02595718
22.
Robins J. 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. 1986;7(9-12):1393-1512. doi:10.1016/0270-0255(86)90088-6
23.
Berkane M. Latent Variable Modeling and Applications to Causality. Vol 120. Springer http://encore.lib.warwick.ac.uk/iii/encore/record/C__Rb3211176
24.
Scheines R, Spirtes P, Glymour C, Meek C, Richardson T. TETRAD 3: Tools for Causal Modeling. User’s Manual. http://www.phil.cmu.edu/tetrad/
25.
Shafer G. The Art of Causal Conjecture. Vol Artificial intelligence. MIT Press; 1996.
26.
Spirtes P, Glymour CN, Scheines R. Causation, Prediction, and Search. Vol Adaptive computation and machine learning. 2nd ed. MIT Press; 2000.
27.
Spirtes P, Glymour CN, Scheines R. Causation, Prediction, and Search. Vol Adaptive computation and machine learning. 2nd edition. The MIT Press; 2000. http://0-cognet.mit.edu.pugwash.lib.warwick.ac.uk/book/causation-prediction-and-search
28.
Studený M. Probabilistic Conditional Independence Structures. Vol Information science and statistics. Springer; 2005. http://0-link.springer.com.pugwash.lib.warwick.ac.uk/10.1007/b138557
29.
Studený M. Probabilistic Conditional Independence Structures. Vol Information science and statistics. Springer; 2005.
30.
Smith JQ, Anderson PE. Conditional independence and chain event graphs. Artificial Intelligence. 2008;172(1):42-68. doi:10.1016/j.artint.2007.05.004
31.
Smith JQ. Bayesian Decision Analysis: Principles and Practice. Cambridge University Press; 2010. http://0-dx.doi.org.pugwash.lib.warwick.ac.uk/10.1017/CBO9780511779237
32.
Smith JQ. Bayesian Decision Analysis: Principles and Practice. Cambridge University Press; 2010.
33.
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; 2006.
34.
Thwaites PA, Smith JQ. Evaluating Causal effects using Chain Event Graphs. In: The Third Workshop on Probabilistic Graphical Models. ; :291-300. http://www.utia.cas.cz/files/mtr/pgm06/18_paper.pdf
