Bibliography for ST413: Bayesian Statistics & Decision Theory with Advanced Topics BETA

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). Available at: http://wrap.warwick.ac.uk/35587/.

Barndorff-Nielsen, O.E., Cox, D.R. and Klüppelberg, C. (no date) Complex stochastic systems [electronic resource]. Boca Raton: Chapman & Hall/CRC. Available at: http://0-marc.crcnetbase.com.pugwash.lib.warwick.ac.uk/isbn/9781420035988.

Berkane, M. (no date) Latent variable modeling and applications to causality. New York: Springer. Available at: http://encore.lib.warwick.ac.uk/iii/encore/record/C__Rb3211176.

Bonet, B. (2001a) ‘A Calculus for Causal Relevance’, in Proceedings of the Seventeen Conference on Uncertainty in Artificial Intelligence. S. Francisco: Morgan Kaufmann, pp. 40–47. Available at: http://arxiv.org/abs/1301.2257?

Bonet, B. (2001b) ‘Instrumentality Tests Revisited’, in Proceedings of the Seventeen Conference on Uncertainty in Artificial Intelligence. S. Francisco: Morgan Kaufmann Publishers, pp. 48–54. Available at: http://arxiv.org/abs/1301.2258?

Capani, A., Niesi, G. and Robbiano, L. (2000) ‘CoCoA 4. a system for doing Computations in Commutative Algebra’. Available at: http://cocoa.dima.unige.it.

Char, B.W. (1991) Maple V library reference manual. New York: Springer-Verlag.

Cooper, G.F. and Glymour, C.N. (eds) (1999) Computation, causation, and discovery. Cambridge, Massachusetts: The MIT Press. Available at: http://0-cognet.mit.edu.pugwash.lib.warwick.ac.uk/book/computation-causation-and-discovery.

Cox, D.R., Klüppelberg, C. and Barndorff-Nielsen, O.E. (2001) Complex stochastic systems. Boca Raton, Fla: Chapman & Hall/CRC.

Dawid, A.P. (2000) ‘Causal Inference Without Counterfactuals’, Journal of the American Statistical Association, 95(450), pp. 407–424. Available at: http://0-www.jstor.org.pugwash.lib.warwick.ac.uk/stable/2669377.

Dawid, A.P. (2002) ‘Influence Diagrams for Causal Modelling and Inference’, International Statistical Review / Revue Internationale de Statistique, 70(2), pp. 161–189. Available at: http://0-www.jstor.org.pugwash.lib.warwick.ac.uk/stable/1403901.

Gale, W.A., AT & T Bell Laboratories, and Workshop on Artificial Intelligence and Statistics (1986) Artificial intelligence and statistics. Reading, Mass: Addison-Wesley Pub. Co.

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 (2006). Paris: EDK.

Mond, D., Riccomagno, E. and Smith, J.Q. (2007) ‘Algebraic causality : Bayes nets and beyond’, Centre for Research in Statistical Methodology. Working papers, Vol.2007 (No.13). Available at: http://wrap.warwick.ac.uk/35544.

Monroy, R. and Mexican International Conference on Artificial Intelligence (no date a) MICAI 2004: advances in artificial intelligence : Third Mexican International Conference on Artificial Intelligence, Mexico City, Mexico, April 26-30, 2004 : proceedings. Berlin: Springer-Verlag. Available at: https://0-link-springer-com.pugwash.lib.warwick.ac.uk/10.1007/b96521.

Monroy, R. and Mexican International Conference on Artificial Intelligence (no date b) MICAI 2004: advances in artificial intelligence : Third Mexican International Conference on Artificial Intelligence, Mexico City, Mexico, April 26-30, 2004 : proceedings. Berlin: Springer-Verlag. Available at: https://0-link-springer-com.pugwash.lib.warwick.ac.uk/10.1007/b96521.

Pearl, J. (1993) ‘Comment: Graphical Models, Causality and Intervention’, Statistical Science, 8(3), pp. 266–269. Available at: http://0-www.jstor.org.pugwash.lib.warwick.ac.uk/stable/2245965.

Pearl, J. (1995) ‘Causal Diagrams for Empirical Research’, Biometrika, 82(4), pp. 669–688. Available at: http://0-www.jstor.org.pugwash.lib.warwick.ac.uk/stable/2337329.

Pearl, J. (2000) Causality: models, reasoning, and inference. Cambridge: Cambridge University Press.

Pearl, J. (2003) ‘Statistics and causal inference: A review’, Test, 12(2), pp. 281–345. Available at: https://doi.org/10.1007/BF02595718.

Proceedings of the 10th Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (2004). Università La Sapienza.

Pronzato, L. and Zhigli︠a︡vskiĭ, A.A. (2008) Optimal design and related areas in optimization and statistics. New York: Springer. Available at: http://0-link.springer.com.pugwash.lib.warwick.ac.uk/chapter/10.1007%2F978-0-387-79936-0_6.

Riccomagno, E. and Smith, J.Q. (2005) ‘The causal manipulation and Bayesian estimation of chain event graphs’. Available at: http://wrap.warwick.ac.uk/35590/.

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), pp. 1393–1512. Available at: https://doi.org/10.1016/0270-0255(86)90088-6.

Scheines, R. et al. (no date) TETRAD 3: Tools for Causal Modeling. User’s Manual. Available at: http://www.phil.cmu.edu/tetrad/.

Shafer, G. (1996) The art of causal conjecture. Cambridge, Mass: MIT Press.

Smith, Jim Q. (2010) Bayesian Decision Analysis: Principles and Practice. Cambridge: Cambridge University Press. Available at: http://0-dx.doi.org.pugwash.lib.warwick.ac.uk/10.1017/CBO9780511779237.

Smith, J. Q. (2010) Bayesian decision analysis: principles and practice. Cambridge: Cambridge University Press.

Smith, J.Q. and Anderson, P.E. (2008) ‘Conditional independence and chain event graphs’, Artificial Intelligence, 172(1), pp. 42–68. Available at: https://doi.org/10.1016/j.artint.2007.05.004.

Spirtes, P., Glymour, C.N. and Scheines, R. (2000a) Causation, prediction, and search. 2nd ed. Cambridge, Mass: MIT Press.

Spirtes, P., Glymour, C.N. and Scheines, R. (2000b) Causation, prediction, and search. 2nd edition. Cambridge, Massachusetts: The MIT Press. Available at: http://0-cognet.mit.edu.pugwash.lib.warwick.ac.uk/book/causation-prediction-and-search.

Studený, M. (2005a) Probabilistic conditional independence structures [electronic resource]. London: Springer. Available at: http://0-link.springer.com.pugwash.lib.warwick.ac.uk/10.1007/b138557.

Studený, M. (2005b) Probabilistic conditional independence structures. London: Springer.

Thwaites, P.A. and Smith, J.Q. (no date) ‘Evaluating Causal effects using Chain Event Graphs’, in The third Workshop on Probabilistic Graphical Models, pp. 291–300. Available at: http://www.utia.cas.cz/files/mtr/pgm06/18_paper.pdf.