Order Statistics from the Power Lindley Distribution and Associated Inference with Application
Devendra Kumar () and
Anju Goyal
Additional contact information
Devendra Kumar: Central University of Haryana
Anju Goyal: Panjab University
Annals of Data Science, 2019, vol. 6, issue 1, No 8, 153-177
Abstract:
Abstract Power Lindley distribution has been proposed recently by Ghitany et al. (Comput Stat Data Anal 64:20–33, 2013) as a simple and useful reliability model for analysing lifetime data. This model provides more flexibility than the Lindley distribution in terms of the shape of the density and hazard rate functions as well as its skewness and kurtosis. For this distribution, exact explicit expressions for single moments, product moments, marginal moment generating functions and joint moment generating functions of each of these order statistics are derived. By using these relations, we have tabulated the expected values, second moments, variances and covariances of order statistics from samples of sizes up to 10 for various values of the parameters. In addition, we use these moments to obtain the best linear unbiased estimates of the location and scale parameters based on Type-II right-censored samples. In addition, we carry out some numerical illustrations through Monte Carlo simulations to show the usefulness of the findings. Finally, we apply the findings of the paper to some real data set.
Keywords: Power Lindley distribution; Order statistics; Single moment; Double moment; Type-II right censoring; Best linear unbiased estimator (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://link.springer.com/10.1007/s40745-019-00193-9 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:6:y:2019:i:1:d:10.1007_s40745-019-00193-9
Ordering information: This journal article can be ordered from
https://www.springer ... gement/journal/40745
DOI: 10.1007/s40745-019-00193-9
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 ().