Estimation of reliability in multicomponent stress-strength model based on Gompertz distribution

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yagoobzadeh shahram

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Journal: ADVANCES IN MATHEMATICAL MODELING Year:2019 | Volume:9 | Issue:2 Page(s): 33-76

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Title

Estimation of reliability in multicomponent stress-strength model based on Gompertz distribution

Author(s)

yagoobzadeh shahram | Issue Writer Certificate

Keywords

Stress–StrengthQ1

ReliabilityQ1

Maximum likelihood estimationQ1

Bayesian estimationQ1

Mean square errorQ1

Gompertz distributionQ1

Abstract

In this research article, we estimate the multicomponent stress– strength Reliability of a system when strength and stress variates are drawn from an exponentiated Weibull distribution with different shape parameters and, and common scale parameter, respectively. The Reliability is estimated using the best single observation percentile method and maximum liklihood method of estimation when samples drawn from strength and stress distributions. The Reliability estimators are compared asymptotically. The small sample comparison of the Reliability estimates is made through Monte Carlo simulation. Using real data sets we illustrate the procedure. Keywords: Stress– Strength, Reliability, Maximum likelihood estimation, Best single observation percentile estimation, Mean square error, Confidence intervals, Gompertz distribution.

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APA: Copy

yagoobzadeh, shahram. (2019). Estimation of reliability in multicomponent stress-strength model based on Gompertz distribution. ADVANCES IN MATHEMATICAL MODELING, 9(2 ), 33-76. SID. https://sid.ir/paper/243872/en

Vancouver: Copy

yagoobzadeh shahram. Estimation of reliability in multicomponent stress-strength model based on Gompertz distribution. ADVANCES IN MATHEMATICAL MODELING[Internet]. 2019;9(2 ):33-76. Available from: https://sid.ir/paper/243872/en

IEEE: Copy

shahram yagoobzadeh, “Estimation of reliability in multicomponent stress-strength model based on Gompertz distribution,” ADVANCES IN MATHEMATICAL MODELING, vol. 9, no. 2 , pp. 33–76, 2019, [Online]. Available: https://sid.ir/paper/243872/en

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