Abstract
This paper deals with the estimation of the stress-strength reliability parameter R = P(Y < X), when X and Y are independent random variables, where X and Y have inverted gamma distribution. The maximum likelihood estimator and the approximate maximum likelihood estimator of R are obtained. The Bayesian estimation of the reliability parameter has been also discussed under the assumption of independent gamma prior, squared error loss and Linex error loss functions. Finally, two real data applications are given for showing the flexibility and potentiality of the inverted gamma distribution.
Highlights
In statistical literature the gamma distribution has been the subject of considerable interest, study, and applications for many years in different areas such as medicine, engineering, economics and Bayesian analysis
This paper deals with the estimation of the stress-strength reliability parameter R 1⁄4 PðY\XÞ, when X and Y are independent random variables, where X and Y have inverted gamma distribution
The Bayesian estimation of the reliability parameter has been discussed under the assumption of independent gamma prior, squared error loss and Linex error loss functions
Summary
On the estimation of stress strength reliability parameter of inverted gamma distribution Anis Iranmanesh1 Kianoosh Fathi Vajargah2 Maryam Hasanzadeh. Received: 21 November 2017 / Accepted: 10 February 2018 / Published online: 6 March 2018 Ó The Author(s) 2018.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
