dc.contributor.author | Cobb, Barry R. | |
dc.contributor.author | Shenoy, Prakash P. | |
dc.date.accessioned | 2005-06-08T16:58:17Z | |
dc.date.available | 2005-06-08T16:58:17Z | |
dc.date.issued | 2005-06 | |
dc.identifier.citation | Cobb, B. R. and P. P. Shenoy (2005), "Inference in Hybrid Bayesian Networks with Mixtures of Truncated Exponentials," University of Kansas School of Business Working Paper No. 294, July 2003, Revised June 2005, Lawrence, KS. | |
dc.identifier.uri | http://hdl.handle.net/1808/467 | |
dc.description | Has been accepted for publication in the International Journal of Approximate Reasoning, Elsevier Science Publishing Co., Inc. | |
dc.description.abstract | Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for solving hybrid Bayesian networks. Any probability density function (PDF) can be approximated with an MTE potential, which can always be marginalized in closed form. This allows propagation to be done exactly using the Shenoy-Shafer architecture for computing marginals, with no restrictions on the construction of a join tree. This paper presents MTE potentials that approximate an arbitrary normal PDF with any mean and a positive variance. The properties of these MTE potentials are presented, along with examples that demonstrate their use in solving hybrid Bayesian networks. Assuming that the joint density exists, MTE potentials can be used for inference in hybrid Bayesian networks that do not fit the restrictive assumptions of the conditional linear Gaussian (CLG) model, such as networks containing discrete nodes with continuous parents. | |
dc.format.extent | 443794 bytes | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | |
dc.publisher | University of Kansas School of Business | |
dc.relation.ispartofseries | School of Business Working Paper;294 | |
dc.subject | Hybrid Bayesian networks | |
dc.subject | Mixtures of truncated exponentials | |
dc.subject | Shenoy-Shafer architecture | |
dc.subject | Conditional linear gaussian models | |
dc.title | Inference in Hybrid Bayesian Networks with Mixtures of Truncated Exponentials | |
dc.type | Working Paper | |
kusw.oastatus | na | |
dc.identifier.orcid | https://orcid.org/0000-0002-8425-896X | |
kusw.oapolicy | This item does not meet KU Open Access policy criteria. | |
dc.rights.accessrights | openAccess | |