Normative selection of Bayesian networks

Paola Sebastiani and Marco Ramoni

Journal of Multivariate Analysis, 2005, vol. 93, issue 2, 340-357

Abstract: This paper presents a Bayesian decision theoretic foundation to the selection of a Bayesian network from data. We introduce the class of disintegrable loss functions to diversify the loss incurred in choosing different models. Disintegrable loss functions can iteratively be built from simple 0-L loss functions over pair-wise model comparisons and decompose the search for the model with minimum risk into a sequence of local searches, thus retaining the modularity of the model selection procedures for Bayesian networks.

Keywords: Bayesian; networks; Directed; acyclic; graphs; Decision; theory; Model; selection (search for similar items in EconPapers)
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047-259X(04)00043-0
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:93:y:2005:i:2:p:340-357

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().