next up previous
Up: Robustness Analysis of Bayesian Previous: Acknowledgements

References

Berger & Moreno1994
Berger, J., and Moreno, E. 1994. Bayesian robustness in bidimensional model: Prior independence. Journal of Statistical Planning and Inference 40:161-176.

Berger1985
Berger, J. O. 1985. Statistical Decision Theory and Bayesian Analysis. Springer-Verlag.

Berger1990
Berger, J. O. 1990. Robust bayesian analysis: Sensitivity to the prior. Journal of Statistical Planning and Inference 25:303-328.

Breese & Fertig1991
Breese, J. S., and Fertig, K. W. 1991. Decision making with interval influence diagrams. In Bonissone, P. P.; Henrion, M.; Kanal, L. N.; and Lemmer, J. F., eds., Uncertainty in Artificial Intelligence 6. North-Holland: Elsevier Science. 467-478.

Cannings & Thompson1981
Cannings, C., and Thompson, E. A. 1981. Genealogical and Genetic Structure. Cambridge: Cambridge University Press.

Cano, Delgado, & Moral1993
Cano, J.; Delgado, M.; and Moral, S. 1993. An axiomatic framework for propagating uncertainty in directed acyclic networks. International Journal of Approximate Reasoning 8:253-280.

Chrisman1996a
Chrisman, L. 1996a. Independence with lower and upper probabilities. Proc. Twelfth Conference Uncertainty in Artificial Intelligence 169-177.

Chrisman1996b
Chrisman, L. 1996b. Propagation of 2-monotone lower probabilities on an undirected graph. Proc. Twelfth Conference Uncertainty in Artificial Intelligence 178-186.

Cozman1996
Cozman, F. 1996. Robust analysis of bayesian networks with finitely generated convex sets of distributions. Technical Report CMU-RI-TR96-41, Carnegie Mellon University.

Dechter1996
Dechter, R. 1996. Bucket elimination: A unifying framework for probabilistic inference. Proc. of the Twelfth Conference Uncertainty in Artificial Intelligence 211-219.

DeRobertis & Hartigan1981
DeRobertis, L., and Hartigan, J. A. 1981. Bayesian inference using intervals of measures. The Annals of Statistics 9(2):235-244.

Giron & Rios1980
Giron, F. J., and Rios, S. 1980. Quasi-bayesian behaviour: A more realistic approach to decision making? In Bernardo, J. M.; DeGroot, J. H.; Lindley, D. V.; and Smith, A. F. M., eds., Bayesian Statistics. Valencia, Spain: University Press. 17-38.

Huber1980
Huber, P. J. 1980. Robust Statistics. New York: Wiley.

Kadane1984
Kadane, J. B. 1984. Robustness of Bayesian Analyses, volume 4 of Studies in Bayesian econometrics. New York: Elsevier Science Pub. Co.

Lavine1991
Lavine, M. 1991. Sensitivity in bayesian statistics, the prior and the likelihood. Journal of the American Statistical Association 86(414):396-399.

Pearl1988
Pearl, J. 1988. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. San Mateo, CA: Morgan Kauffman.

Seidenfeld & Wasserman1993
Seidenfeld, T., and Wasserman, L. 1993. Dilation for sets of probabilities. The Annals of Statistics 21(9):1139-1154.

Shenoy & Shafer1990
Shenoy, P. P., and Shafer, G. 1990. Axioms for probability and belief-function propagation. In Shachter, R. D.; Levitt, T. S.; Kanal, L. N.; and Lemmer, J. F., eds., Uncertainty in Artificial Intelligence 4. North-Holland: Elsevier Science Publishers. 169-198.

Tessem1992
Tessem, B. 1992. Interval probability propagation. International Journal of Approximate Reasoning 7:95-120.

Walley1991
Walley, P. 1991. Statistical Reasoning with Imprecise Probabilities. New York: Chapman and Hall.

Wasserman & Kadane1992
Wasserman, L., and Kadane, J. B. 1992. Computing bounds on expectations. Journal of the American Statistical Association 87(418):516-522.

Wasserman1990
Wasserman, L. A. 1990. Prior envelopes based on belief functions. The Annals of Statistics 18(1):454-464.

Wasserman1992a
Wasserman, L. 1992a. Invariance properties of density ratio priors. The Annals of Statistics 20(4):2177-2182.

Wasserman1992b
Wasserman, L. 1992b. Recent methodological advances in robust bayesian inference. In Bernardo, J. M.; Berger, J. O.; Dawid, A. P.; and Smith, A. F. M., eds., Bayesian Statistics 4. Oxford University Press. 483-502.

York1992
York, J. 1992. Use of the gibbs sampler in expert systems. Artificial Intelligence 56:115-130.

Zhang & Poole1996
Zhang, N. L., and Poole, D. 1996. Exploiting causal independence in Bayesian network inference. Journal of Artificial Intelligence Research 301-328.



© Fabio Cozman[Send Mail?]

Thu Jan 23 15:54:13 EST 1997