On measures of extropy for conditionally specified models: Some results
Indranil Ghosh,
S.M. Sunoj and
P. Saranya
Communications in Statistics - Theory and Methods, 2025, vol. 54, issue 16, 5057-5081
Abstract:
This article introduces extropy measures for conditionally specified probability models, in particular, for the hidden truncation models. Based on the associated extropy measure, a new measure on discriminating between a hidden truncated version of a random variable with that of a non truncated version is developed. A broad collection of hidden truncation models is utilized to derive the associated extropy measures. Some characterization theorems using extropy and cumulative residual extropy are also discussed. Several examples are presented throughout to illustrate the various concepts on conditionally specified extropy models.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2024.2430747 (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:54:y:2025:i:16:p:5057-5081
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2024.2430747
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 ().