Nonlinear deterministic relationships in Bayesian networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3571 LNAI, Issue , 2005, Pages 27-38

  Cobb, Barry R ^a   Shenoy, Prakash P ^a  

^a UNIVERSITY OF KANSAS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GAUSSIAN NOISE (ELECTRONIC); MATHEMATICAL MODELS; MULTIVARIABLE CONTROL SYSTEMS; PROBABILITY DENSITY FUNCTION; STATISTICAL METHODS;

LINEAR APPROXIMATIONS; MIXTURES OF TRUNCATED EXPONENTIALS (MTE) POTENTIALS; MULTI-VARIATE NORMAL DISTRIBUTION; NON-GAUSSIAN CONTINUOUS VARIABLES;

NONLINEAR SYSTEMS;

EID: 26944472022     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11518655_4     Document Type: Conference Paper

References (7)

1. Cobb, B.R. and P.P. Shenoy: Inference in hybrid Bayesian networks with deterministic variables. In P. Lucas (ed.): Proceedings of the Second European Workshop on Probabilistic Graphical Models (PGM-04) (2004) 57-64, Leiden, Netherlands.
2. Cobb, B.R. and P.P. Shenoy: Modeling nonlinear deterministic relationships in Bayesian networks. School of Business Working Paper No. 310, University of Kansas, Lawrence, Kansas (2005). Available for download at: http://www.people.ku.edu/~brcobb/WP310.pdf
3. Cobb, B.R., Shenoy, P.P. and R. Rumí: Approximating probability density functions in hybrid Bayesian networks with mixtures of truncated exponentials. Working Paper No. 303, School of Business, University of Kansas, Lawrence, Kansas (2003). Available for download at: http://www.people.ku.edu/ ~brcobb/WP303.pdf
4. Kullback, S. and R.A. Leibler: On information and sufficiency. Annals of Mathematical Statistics 22 (1951) 79-86.
5. Larsen, R.J. and M.L. Marx: An Introduction to Mathematical Statistics and its Applications (2001) Prentice Hall, Upper Saddle River, N.J.
6. S.L. Lauritzen and F. Jensen: Stable local computation with conditional Gaussian distributions. Statistics and Computing 11 (2001) 191-203.
7. Moral, S., Rumí, R. and A. Salmerón: Mixtures of truncated exponentials in hybrid Bayesian networks. In P. Besnard and S. Benferhart (eds.): Symbolic and Quantitative Approaches to Reasoning under Uncertainty, Lecture Notes in Artificial Intelligence 2143 (2001) 156-167, Springer-Verlag, Heidelberg.