Kernel estimation of extropy function under length-biased sampling

Richu Rajesh, Rajesh G. and S.M. Sunoj

Statistics & Probability Letters, 2022, vol. 181, issue C

Abstract: In this article, we address the problem of nonparametric kernel estimators of extropy function under length-biased sampling. The large sample properties of the proposed estimators namely, the consistency and asymptotic normality are verified under suitable regularity conditions. In addition, the finite sample behaviour of the proposed estimators is investigated via a simulation study. Application to real data is also reported.

Keywords: Extropy; Length-biased sample; Kernel estimation; Root mean squared error (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715221002522
Full text for ScienceDirect subscribers only

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:eee:stapro:v:181:y:2022:i:c:s0167715221002522

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.spl.2021.109290

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().