Moments of Order Statistics from Length-Biased Exponential Distribution and Associated Inference

Zuber Akhter (), Jagdish Saran, Kanika Verma and Narinder Pushkarna
Additional contact information
Zuber Akhter: University of Delhi
Jagdish Saran: University of Delhi
Kanika Verma: University of Delhi
Narinder Pushkarna: University of Delhi

Annals of Data Science, 2022, vol. 9, issue 6, No 8, 1257-1282

Abstract: Abstract Dara and Ahmad (Recent advances in moment distribution and their hazard rates, Academic Publishing GmbH KG, Lap Lambert, 2012) proposed the length-biased exponential (LBE) distribution and proved that the LBE distribution is more flexible than the exponential distribution. In this paper, we have obtained new explicit algebraic expressions and some recurrence relations for both single and product moments of order statistics from LBE distribution. Further, these expressions are used to compute the means, variances and covariances of order statistics for different sample of sizes and for arbitrarily chosen parameter values. Next, we use these moments to obtain the best linear unbiased estimates of the location and scale parameters based on complete as well as Type-II right censored samples. Finally, we carried out a simulation study to show the application of our results.

Keywords: Best linear unbiased estimation; Length-biased exponential (LBE) distribution; Order statistics; Single moments; Product moments; Recurrence relations; 62G30 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s40745-020-00245-5 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:aodasc:v:9:y:2022:i:6:d:10.1007_s40745-020-00245-5

Ordering information: This journal article can be ordered from
https://www.springer ... gement/journal/40745

DOI: 10.1007/s40745-020-00245-5

Access Statistics for this article

Annals of Data Science is currently edited by Yong Shi

More articles in Annals of Data Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().