Optimal Quantization of the Support of a Continuous Multivariate Distribution based on Mutual Information
Bernard Colin (),
François Dubeau,
Hussein Khreibani and
Jules Tibeiro
Journal of Classification, 2013, vol. 30, issue 3, 453-473
Abstract:
Based on the notion of mutual information between the components of a random vector, we construct, for data reduction reasons, an optimal quantization of the support of its probability measure. More precisely, we propose a simultaneous discretization of the whole set of the components of the random vector which takes into account, as much as possible, the stochastic dependence between them. Examples are presented. Copyright Springer Science+Business Media New York 2013
Keywords: Divergence; Mutual information; Copula; Optimal quantization (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1007/s00357-013-9127-6 (text/html)
Access to full text is restricted to subscribers.
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:spr:jclass:v:30:y:2013:i:3:p:453-473
Ordering information: This journal article can be ordered from
http://www.springer. ... hods/journal/357/PS2
DOI: 10.1007/s00357-013-9127-6
Access Statistics for this article
Journal of Classification is currently edited by Douglas Steinley
More articles in Journal of Classification from Springer, The Classification Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().