The Complementary Lindley-Geometric Distribution and Its Application in Lifetime Analysis

Wenhao Gui (), Huainian Zhang and Lei Guo
Additional contact information
Wenhao Gui: Beijing Jiaotong University
Huainian Zhang: Beijing Institute of Petro-chemical Technology
Lei Guo: Beijing Jiaotong University

Sankhya B: The Indian Journal of Statistics, 2017, vol. 79, issue 2, No 7, 316-335

Abstract: Abstract In this paper, we propose a new compounding distribution, named the complementary Lindley-geometric distribution. It arises on a latent complementary risks scenarios where only the maximum lifetime value among all risks instead of a particular risk is observed. Its characterization and statistical properties are investigated. The maximum likelihood inference using EM algorithm is developed. Asymptotic properties of the MLEs are discussed and simulation studies are performed to assess the performance of parameter estimation. We illustrate the proposed model with a real application and it shows that the new distribution is appropriate and potential for lifetime analyses.

Keywords: Lindley distribution; Geometric distribution; Hazard function; Maximum likelihood estimation; EM algorithm; Fisher information matrix; Primary 62E15; Secondary 62F10 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s13571-017-0142-1 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:sankhb:v:79:y:2017:i:2:d:10.1007_s13571-017-0142-1

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/13571

DOI: 10.1007/s13571-017-0142-1

Access Statistics for this article

Sankhya B: The Indian Journal of Statistics is currently edited by Dipak Dey

More articles in Sankhya B: The Indian Journal of Statistics from Springer, Indian Statistical Institute
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().