EconPapers    
Economics at your fingertips  
 

On the distribution of Gini’s rank association index

Yiwei Zong, Ffion Loring and William F. Scott

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 21, 7788-7796

Abstract: Gini’s rank association index is a non parametric measure of association, and is fully described by Genest, Nešlehová and Ben Ghorbal (2010). In this article, we compute the null distribution of this index up to n = 28 where n is the sample size. Our methods are based on permanents and extend the results of Betro (1993). We also discuss approximations to the null distribution for large n. We believe that Gini’s rank association index should be more widely used; in particular, it may be preferable to Spearman’s rank correlation coefficient if the bivariate distribution is such that outliers are quite likely to occur.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2022.2071942 (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:lstaxx:v:52:y:2023:i:21:p:7788-7796

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2022.2071942

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:lstaxx:v:52:y:2023:i:21:p:7788-7796