Bibliography

1

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

2

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

3

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

4

E. Charniak.
Bayesian networks without tears.
AI Magazine, 1991.

5

G. F. Cooper.
The computational complexity of probabilistic inference using Bayesian belief networks.
Artificial Intelligence, 42:393-405, 1990.

6

R. Dechter.
Bucket elimination: a unifying framework for probabilistic inference.
Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996.

7

M. DeGroot.
Optimal Statistical Decisions.
McGraw-Hill, New York, 1970.

8

J. Earman.
Bayes or Bust?
The MIT Press, Cambridge, MA, 1992.

9

F. V. Jensen.
An Introduction to Bayesian Networks.
Springer Verlag, New York, 1996.

10

U. Kjaerulff.
Triangulation of graphs -- algorithms giving small total state space.
Technical Report R-90-09, Department of Mathematics and Computer Science, Aalborg University, Denmark, March 1990.

11

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

12

J. Pearl.
On probability intervals.
Int. Journal of Approximate Reasoning, 2:211-216, 1988.

13

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

14

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

15

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