Bivariate degradation analysis of products based on Wiener processes and copulas

DOI10.1080/00949655.2012.658805zbMath1431.62461OpenAlexW1995373625MaRDI QIDQ5218868

Zhengqiang Pan, Quan Sun, Jing Lun Zhou, Narayanaswamy Balakrishnan

Publication date: 6 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2012.658805

zbMATH Keywords

Wiener processcopula functionperformance characteristicbivariate degradationBayesian MCMC method

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Computational methods for problems pertaining to statistics (62-08) Markov processes: estimation; hidden Markov models (62M05) Estimation in survival analysis and censored data (62N02) Reliability and life testing (62N05)

Related Items (17)

Nonparametric optimal designs for degradation tests ⋮ Bayesian Analysis of a New Bivariate Wiener Degradation Process ⋮ A time-discrete and zero-adjusted gamma process model with application to degradation analysis ⋮ Degradation-Based Reliability Modeling of Complex Systems in Dynamic Environments ⋮ Inverse Gaussian process models for bivariate degradation analysis: A Bayesian perspective ⋮ Copula models for one-shot device testing data with correlated failure modes ⋮ Reliability and availability analysis of stochastic degradation systems based on bivariate Wiener processes ⋮ Bivariate degradation modelling with marginal heterogeneous stochastic processes ⋮ Degradation model analysis of two-component series and parallel systems ⋮ CUSUM control schemes for monitoring Wiener processes ⋮ Bivariate nonlinear diffusion degradation process modeling via copula and MCMC ⋮ Reliability modeling for systems with multiple degradation processes using inverse Gaussian process and copulas ⋮ Objective Bayesian analysis for competing risks model with Wiener degradation phenomena and catastrophic failures ⋮ Optimal step-stress accelerated degradation test plans for inverse Gaussian process based on proportional degradation rate model ⋮ Residual life estimation based on bivariate Wiener degradation process with time-scale transformations ⋮ Residual life estimation based on bivariate non-stationary gamma degradation process ⋮ Reliability assessment for products with two performance characteristics based on marginal stochastic processes and copulas

Uses Software

• WinBUGS

Cites Work

• Unnamed Item
• Statistical analysis of linear degradation and failure time data with multiple failure modes
• An introduction to copulas.
• Wiener processes with random effects for degradation data
• Modelling accelerated degradation data using Wiener diffusion with a time scale transformation
• Accelerated test models with the inverse Gaussian distribution
• A review of accelerated test models
• Analysis of joint multiple failure mode and linear degradation data with renewals
• Bayesian Modeling Using WinBUGS

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