Staff Members - Benha University
Stress-Strength Reliability Estimation for Exponentiated Generalized Inverse Weibull Distribution
Journal of Statistics Applications & Probability • 2018
Publication Information
Authors
M. M. Mohie El-Din, A. Sadek, and Sh. H. Elmeghawry
Keywords
Exponentiated generalized inverse Weibull distribution, Stress-strength reliability, Maximum likelihood estimation,
Bayesian estimation, Importance sampling technique
Journal
Journal of Statistics Applications & Probability
Publisher
Natural Sciences Publishing Cor.
Volume
Vol. 7
Issue
Not Available
Pages
127-136
publication.type
International
Paper Link
Open Link
Supplementary Materials
Not Available
Abstract
This paper is devoted to discuss the stress-strength reliability model R = Pr (Y < X) when X and Y have an exponentiated
generalized inverse Weibull distribution (EGIW) with different parameters. The problem of stress-strength reliability is studied to
obtain estimates of a component reliability function of EGIW distribution. Reliability for multi-component stress-strength model for
EGIW distribution is also studied. Maximum likelihood estimation for stress-strength reliability of underlying distribution is
performed. Bayesian estimator of R is obtained using importance sampling technique. A simulation study to investigate and compare
the performance of each method of estimation is performed. Finally analysis of a real data set has also been presented for illustrative
purposes.
generalized inverse Weibull distribution (EGIW) with different parameters. The problem of stress-strength reliability is studied to
obtain estimates of a component reliability function of EGIW distribution. Reliability for multi-component stress-strength model for
EGIW distribution is also studied. Maximum likelihood estimation for stress-strength reliability of underlying distribution is
performed. Bayesian estimator of R is obtained using importance sampling technique. A simulation study to investigate and compare
the performance of each method of estimation is performed. Finally analysis of a real data set has also been presented for illustrative
purposes.