EconPapers    
Economics at your fingertips  
 

Some results on the computing of Tukey’s halfspace median

Xiaohui Liu (), Shihua Luo and Yijun Zuo
Additional contact information
Xiaohui Liu: Jiangxi University of Finance and Economics
Shihua Luo: Jiangxi University of Finance and Economics
Yijun Zuo: Michigan State University

Statistical Papers, 2020, vol. 61, issue 1, No 16, 303-316

Abstract: Abstract Depth of the Tukey median is investigated for empirical distributions. A sharper upper bound is provided for this value for data sets in general position. This bound is lower than the existing one in the literature and, more importantly, derived under the fixed sample size practical scenario. Several results obtained in this paper are interesting theoretically and useful as well to reduce the computational burden of the Tukey median practically when $$p > 2$$p>2.

Keywords: Data depth; Tukey median; Maximum halfspace depth; General position; 62F10; 62F40; 62F35 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00362-017-0941-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:stpapr:v:61:y:2020:i:1:d:10.1007_s00362-017-0941-5

Ordering information: This journal article can be ordered from
http://www.springer. ... business/journal/362

DOI: 10.1007/s00362-017-0941-5

Access Statistics for this article

Statistical Papers is currently edited by C. Müller, W. Krämer and W.G. Müller

More articles in Statistical Papers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:stpapr:v:61:y:2020:i:1:d:10.1007_s00362-017-0941-5