EconPapers    
Economics at your fingertips  
 

Extropy estimators with applications in testing uniformity

Guoxin Qiu and Kai Jia

Journal of Nonparametric Statistics, 2018, vol. 30, issue 1, 182-196

Abstract: Two estimators for estimating the extropy of an absolutely continuous random variable with known support were introduced by using spacing. It is shown that the proposed estimators are consistent and their mean square errors are shift invariant. Their behaviours were also studied by means of real data and Monte Carlo simulation. The winner estimator of extropy in the Monte Carlo experiment was used to develop goodness-of-fit test for standard uniform distribution. It is shown that the extropy-based test that we proposed performs well by comparing its powers with that of other tests for uniformity.

Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1080/10485252.2017.1404063 (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:gnstxx:v:30:y:2018:i:1:p:182-196

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GNST20

Access Statistics for this article

Journal of Nonparametric Statistics is currently edited by Jun Shao

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

 
Page updated 2019-03-23
Handle: RePEc:taf:gnstxx:v:30:y:2018:i:1:p:182-196