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On Bayesian Estimation in a Parallel System
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Gabriela A. Valdés
Published/Copyright:
March 10, 2010
Abstract
This paper presents a Bayesian approach to the estimation of the reliability of a parallel system with k components. It is assumed that the strengths of the k components are subjected to a common stress which is independent of the strengths of the k components. The reliability of the parallel system or system reliability is estimated assuming that the strengths and the stress are exponentially distributed random variables. The performed Bayesian analysis is based on conjugated prior and non-informative prior distributions, respectively. A simulation data set is considered in order to study the performance of the Bayesian solutions. Some observations are discussed concerning alternative methods and possible extensions.
Published Online: 2010-03-10
Published in Print: 2006-October
© Heldermann Verlag
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Articles in the same Issue
- A Note on Run Length Variability Reduction for EWMA Charting
- A Note on Nature and Significance of Stochastic Models
- Estimation of Pareto Survival Function in the Presence of Outlying Observations
- Loss Reduction in Point Estimation Problems
- Application of Arithmetic-Geometric Mean Inequality for Construction of Reliability Test Plan for Parallel Systems in the Presence of Covariates
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- Approximating Reliability of a System with Doubly Bounded Performance Functions
- Probability Weighted Moments Approach to Quality Control Charts
- Weibull Extension of Bivariate Exponential Regression Model with Gamma Frailty for Survival Data
- Nonlinear Tobit Decomposition
- Reliability Test Plans for Exponentiated Log-Logistic Distribution
- Transient Analysis of a System with Queue Dependent Servers and Controllable Arrivals
