EconPapers    
Economics at your fingertips  
 

Clustering probability distributions

Tai Vo Van and T. Pham-Gia

Journal of Applied Statistics, 2010, vol. 37, issue 11, 1891-1910

Abstract: This article presents some theoretical results on the maximum of several functions, and its use to define the joint distance of k probability densities, which, in turn, serves to derive new algorithms for clustering densities. Numerical examples are presented to illustrate the theory.

Keywords: maximum function; cluster; L1-distance; Bayes error; hierarchical approach (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/02664760903186049 (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:taf:japsta:v:37:y:2010:i:11:p:1891-1910

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20

DOI: 10.1080/02664760903186049

Access Statistics for this article

Journal of Applied Statistics is currently edited by Robert Aykroyd

More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:japsta:v:37:y:2010:i:11:p:1891-1910