Estimation of Stress-Strength Reliability for Multicomponent System with Rayleigh Data

Liang Wang, Huizhong Lin, Kambiz Ahmadi and Yuhlong Lio
Additional contact information
Liang Wang: School of Mathematics, Yunnan Normal University, Kunming 650500, China
Huizhong Lin: School of Mathematics, Yunnan Normal University, Kunming 650500, China
Kambiz Ahmadi: Department of Computer Science, Faculty of Mathematical Sciences, Shahrekord University, Shahrekord 115, Iran
Yuhlong Lio: Department of Mathematical Sciences, University of South Dakota, Vermillion, SD 57069, USA

Energies, 2021, vol. 14, issue 23, 1-23

Abstract: Inference is investigated for a multicomponent stress-strength reliability (MSR) under Type-II censoring when the latent failure times follow two-parameter Rayleigh distribution. With a context that the lifetimes of the strength and stress variables have common location parameters, maximum likelihood estimator of MSR along with the existence and uniqueness is established. The associated approximate confidence interval is provided via the asymptotic distribution theory and delta method. Meanwhile, alternative generalized pivotal quantities-based point and confidence interval estimators are also constructed for MSR. More generally, when the lifetimes of strength and stress variables follow Rayleigh distributions with unequal location parameters, likelihood and generalized pivotal-based estimators are provided for MSR as well. In addition, to compare the equivalence of different strength and stress parameters, a likelihood ratio test is provided. Finally, simulation studies and a real data example are presented for illustration.

Keywords: multicomponent stress-strength model; rayleigh distribution; likelihood estimation; generalized pivotal estimation; asymptotic theory (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/23/7917/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/23/7917/ (text/html)

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:gam:jeners:v:14:y:2021:i:23:p:7917-:d:687796

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().