The University of Southampton
University of Southampton Institutional Repository

Dependence tree structure estimation via copula

Ma, Jian, Sun, Zeng-Qi, Chen, Sheng and Liu, Hong-Hai (2012) Dependence tree structure estimation via copula International Journal of Automation and Computing, 9, (2), Spring Issue, pp. 113-121. (doi:10.1007/s11633-012-0624-6).

Record type: Article


We propose an approach for dependence tree structure learning via copula. A nonparametric algorithm for copula estimation is presented. Then a Chow-Liu like method based on dependence measure via copula is proposed to estimate maximum spanning bivariate copula associated with bivariate dependence relations. The main advantage of the approach is that learning with empirical copula focuses on dependence relations among random variables, without the need to know the properties of individual variables as well as without the requirement to specify parametric family of entire underlying distribution for individual variables. Experiments on two real-application data sets show the effectiveness of the proposed method.

PDF IJAC-2012-April.pdf - Version of Record
Restricted to Repository staff only
Download (1MB)

More information

Published date: April 2012
Keywords: copula, empirical copula, dependence, tree structure learning, probability distribution
Organisations: Southampton Wireless Group


Local EPrints ID: 334890
ISSN: 1476-8186
PURE UUID: 536e1195-e403-43b1-b900-d72818b4e97d

Catalogue record

Date deposited: 08 Mar 2012 11:19
Last modified: 18 Jul 2017 06:11

Export record



Author: Jian Ma
Author: Zeng-Qi Sun
Author: Sheng Chen
Author: Hong-Hai Liu

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.