Estimation of stress-strength reliability based on unit generalized Gompertz distribution

Azam Karandishmarvasti, Ehsan Ormoz and Maryam Basirat

Communications in Statistics - Theory and Methods, 2025, vol. 54, issue 15, 4819-4829

Abstract: Although the investigation of the stress-strength parameter has a long history due to its importance, the investigation of this parameter in distributions with a limited range, such as (0, 1), has received less attention. Thus, in this article, we study the stress-strength parameter for Unit Generalized Gompertz (UGG) distribution, which can cover a variety of data, including data skewed ones. Considering the flexibility of the shape of the density function and its hazard rate function, we expect that this distribution would possess more applicability and can be fitted to different data sets. With this aim, we discuss the parameter R for the UGG distribution and obtain different methods of parameter estimation such as maximum likelihood, bootstrap, and Bayesian. The performance of the estimators has been done by simulation, and finally, the presented content has been applied to a real data set.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2024.2428988 (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:15:p:4819-4829

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2024.2428988

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 ().