Likelihood and Bayesian estimation of $$P(Y{
Francesca Condino (),
Filippo Domma and
Giovanni Latorre
Additional contact information
Francesca Condino: University of Calabria
Filippo Domma: University of Calabria
Giovanni Latorre: University of Calabria
Statistical Papers, 2018, vol. 59, issue 2, No 3, 467-485
Abstract:
Abstract In this paper, we study inference for the stress–strength reliability based on lower record data, where the stress and the strength variables are modeled by two independent but not identically distributed random variables from distributions belonging to the proportional reversed hazard family. Likelihood and Bayesian estimators are derived, then confidence intervals and credible sets are obtained. Moreover, we consider the Topp–Leone distribution as a particular case of distribution belonging to this family and we derive some numerical results in order to show the performance of the proposed procedures. Finally, two applications to real data are reported.
Keywords: Reliability; Stress–strength model; Confidence interval; Topp–Leone distribution (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s00362-016-0772-9 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:stpapr:v:59:y:2018:i:2:d:10.1007_s00362-016-0772-9
Ordering information: This journal article can be ordered from
http://www.springer. ... business/journal/362
DOI: 10.1007/s00362-016-0772-9
Access Statistics for this article
Statistical Papers is currently edited by C. Müller, W. Krämer and W.G. Müller
More articles in Statistical Papers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().