Analyzing the dynamic system model with discrete failure time distribution

DOI10.1007/S10260-008-0111-YzbMath1332.62396OpenAlexW2023241926MaRDI QIDQ257527

F. Blanchet-Sadri, M. Dambrine

Publication date: 17 March 2016

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10260-008-0111-y

zbMATH Keywords

Markov chain Monte Carlomaximum likelihood estimatorBayes estimatorGibbs samplerconstant failure-rateshighest posterior density intervalsload-sharing rulesload-sharing systemsquared error loss function

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40) Reliability and life testing (62N05)

Related Items (2)

Load-sharing system model and its application to the real data set ⋮ Inferential statistics on the dynamic system model with time-dependent failure-rate

Cites Work

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• Reliability measures in the discrete bivariate set-up and related characterization results for a bivariate geometric distribution
• Reliability estimation based on system data with an unknown load share rule
• Theoretical comparison of bootstrap confidence intervals
• A threshold representation for the strength distribution of a complex load sharing system
• A model in which component failure rates depend on the working set
• Hazard functions and life distributions in discrete time
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Accurate Approximations for Posterior Moments and Marginal Densities
• Probability distributions for the strength of fibrous materials under local load sharing I: Two-level failure and edge effects
• Monte Carlo sampling methods using Markov chains and their applications
• Estimating Load-Sharing Properties in a Dynamic Reliability System
• The Monte Carlo Method

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