Estimation of reliability in multicomponent stress-strength based on generalized Rayleigh distribution

Rao, Gadde Srinivasa

dc.creator	Rao, Gadde Srinivasa
dc.date	2020-11-25T07:41:11Z
dc.date	2020-11-25T07:41:11Z
dc.date	2014
dc.date.accessioned	2022-10-20T13:09:18Z
dc.date.available	2022-10-20T13:09:18Z
dc.identifier	Rao, G. S. (2014). Estimation of reliability in multicomponent stress-strength based on generalized Rayleigh distribution. Journal of Modern Applied Statistical Methods, 13(1), 367-379.
dc.identifier	DOI: 10.22237/jmasm/1398918180
dc.identifier	http://hdl.handle.net/20.500.12661/2596
dc.identifier.uri	http://hdl.handle.net/20.500.12661/2596
dc.description	Abstract. Full text available at https://digitalcommons.wayne.edu/jmasm/vol13/iss1/24/
dc.description	A multicomponent system of k components having strengths following k- independently and identically distributed random variables x1, x2,…, xk and each component experiencing a random stress Y is considered. The system is regarded as alive only if at least s out of k (s < k) strengths exceed the stress. The reliability of such a system is obtained when strength and stress variates are given by a generalized Rayleigh distribution with different shape parameters. Reliability is estimated using the maximum likelihood (ML) method of estimation in samples drawn from strength and stress distributions; the reliability estimators are compared asymptotically. Monte-Carlo simulation is used to compare reliability estimates for the small samples and real data sets illustrate the procedure.
dc.language	en
dc.publisher	Wayne State University Library System in Detroit
dc.subject	ML estimation
dc.subject	Confidence intervals
dc.subject	Stress-strength
dc.subject	Reliability estimation
dc.subject	Rayleigh distribution
dc.subject	Maximum likelihood
dc.subject	ML
dc.subject	Generalized rayleigh distribution
dc.title	Estimation of reliability in multicomponent stress-strength based on generalized Rayleigh distribution
dc.type	Article