Bivariate nonlinear diffusion degradation process modeling via copula and MCMC
type: Item
instance of: scholarly article
title: Bivariate nonlinear diffusion degradation process modeling via copula and MCMC
zbMATH Open document ID: 1407.62366
DOI: 10.1155/2014/510929
author: Huibing Hao
author: Chun Su
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: A novel reliability assessment method for degradation product with two dependent performance characteristics (PCs) is proposed, which is different from existing work that only utilized one dimensional degradation data. In this model, the dependence of two PCs is described by the Frank copula function, and each PC is governed by a random effected nonlinear diffusion process where random effects capture the unit to unit differences. Considering that the model is so complicated and analytically intractable, Markov Chain Monte Carlo (MCMC) method is used to estimate the unknown parameters. A numerical example about LED lamp is given to demonstrate the usefulness and validity of the proposed model and method. Numerical results show that the random effected nonlinear diffusion model is very useful by checking the goodness of fit of the real data, and ignoring the dependence between PCs may result in different reliability conclusion.
Mathematics Subject Classification ID: 62N05
Mathematics Subject Classification ID: 62H05
Mathematics Subject Classification ID: 65C60
zbMATH DE Number: 7016621
Wikidata QID: Q59068044
describes a project that uses: SPLIDA
describes a project that uses: WinBUGS
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/510929
OpenAlex ID: W1975092019
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description: scientific article; zbMATH DE number 7016621