Semi-parametric Bayesian models for heterogeneous degradation data: An application to laser data
- 3 June 2020
- journal article
- research article
- Published by Elsevier BV in Reliability Engineering & System Safety
- Vol. 202, 107038
- https://doi.org/10.1016/j.ress.2020.107038
Abstract
No abstract availableKeywords
Funding Information
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Pró-Reitoria de Pesquisa, Universidade Federal de Minas Gerais
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Fundação de Amparo à Pesquisa do Estado de Minas Gerais
This publication has 30 references indexed in Scilit:
- Wiener processes with random effects for degradation dataJournal of Multivariate Analysis, 2010
- Bayesian inference for finite mixtures of univariate and multivariate skew-normal and skew-t distributionsBiostatistics, 2010
- Using Degradation Data to Assess ReliabilityQuality Engineering, 2005
- Markov chain Monte Carlo in approximate Dirichlet and beta two-parameter process hierarchical modelsBiometrika, 2000
- Approximating distributions of random functionals of Ferguson‐Dirichlet priorsThe Canadian Journal of Statistics / La Revue Canadienne de Statistique, 1998
- Bayesian Density Estimation and Inference Using MixturesJournal of the American Statistical Association, 1995
- Bayesian Density Estimation and Inference Using MixturesJournal of the American Statistical Association, 1995
- Using Degradation Measures to Estimate a Time-to-Failure DistributionTechnometrics, 1993
- Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric ProblemsThe Annals of Statistics, 1974
- A Bayesian Analysis of Some Nonparametric ProblemsThe Annals of Statistics, 1973