Bivariate nonlinear diffusion degradation process modeling via copula and MCMC

DOI10.1155/2014/510929zbMath1407.62366OpenAlexW1975092019WikidataQ59068044 ScholiaQ59068044MaRDI QIDQ1718567

Chun Su, Huibing Hao

Publication date: 8 February 2019

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2014/510929

Mathematics Subject Classification ID

Characterization and structure theory for multivariate probability distributions; copulas (62H05) Reliability and life testing (62N05)

Related Items (4)

Degradation data analysis and remaining useful life estimation: a review on Wiener-process-based methods ⋮ Bivariate degradation modelling with marginal heterogeneous stochastic processes ⋮ Reliability modeling for systems with multiple degradation processes using inverse Gaussian process and copulas ⋮ Copula-based reliability analysis for a parallel system with a cold standby

Uses Software

• WinBUGS
• SPLIDA

Cites Work

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• Statistical analysis of linear degradation and failure time data with multiple failure modes
• An introduction to copulas.
• Accelerated degradation models for failure based on geometric Brownian motion and gamma processes
• Wiener processes with random effects for degradation data
• Modelling accelerated degradation data using Wiener diffusion with a time scale transformation
• Time-variant reliability assessment and its sensitivity analysis of cutting tool under invariant machining condition based on Gamma process
• An expectation maximization algorithm to model failure times by continuous-time Markov chains
• Analysis of joint multiple failure mode and linear degradation data with renewals
• Bivariate Constant-Stress Accelerated Degradation Model and Inference
• Estimating failure time distribution and its parameters based on intermediate data from a Wiener degradation model
• Bayesian Modeling Using WinBUGS
• Accelerated Testing
• Determination of burn-in parameters and residual life for highly reliable products
• Bivariate degradation analysis of products based on Wiener processes and copulas
• Monte Carlo sampling methods using Markov chains and their applications
• Models for Variable-Stress Accelerated Life Testing Experiments Based on Wiener Processes and the Inverse Gaussian Distribution

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