Likelihood ratio gradient estimation for dynamic reliability applications

Jinghui Li, Ali Mosleh and Rui Kang

Reliability Engineering and System Safety, 2011, vol. 96, issue 12, 1667-1679

Abstract: This paper investigates the issue of performing a first-order sensitivity analysis in the setting of dynamic reliability. The likelihood ratio (LR) derivative/gradient estimation method is chosen to fulfill the mission. Its formulation and implementation in the system-based Monte Carlo approach that is commonly used in dynamic reliability applications is first given. To speed up the simulation, we then apply the LR method within the framework of Z-VISA, a biasing (or importance sampling) method we have developed recently. A widely discussed dynamic reliability example (a holdup tank) is studied to test the effectiveness and behaviors of the LR method when applied to dynamic reliability problems and also the effectiveness of the Z-VISA biasing technique for reducing the variance of LR derivative estimators.

Keywords: Derivative estimation; Likelihood ratio; Monte Carlo simulation; Importance sampling; Importance measure; Dynamic reliability (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:96:y:2011:i:12:p:1667-1679

DOI: 10.1016/j.ress.2011.08.001

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