Remaining useful life prediction: A multiple product partition approach
From MaRDI portal
Publication:5042126
DOI10.1080/03610918.2020.1766499OpenAlexW3027724828MaRDI QIDQ5042126
John W. Lau, Sally Cripps, Edward Cripps
Publication date: 18 October 2022
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2020.1766499
Cites Work
- Unnamed Item
- Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
- A probability for classification based on the Dirichlet process mixture model
- A note on generating random variables with log-concave densities
- Degradation modeling applied to residual lifetime prediction using functional data analysis
- Estimation of a noisy discrete-time step function: Bayes and empirical Bayes approaches
- Accelerated degradation models for failure based on geometric Brownian motion and gamma processes
- Product partition models for change point problems
- Inference from accelerated degradation and failure data based on Gaussian process models
- Reliability evaluation based on a dependent two-stage failure process with competing failures
- Bayesian Value-at-Risk with product partition models
- Bayesian analysis for inverse gaussian lifetime data with measures of degradation
- A Bayesian Analysis for Change Point Problems
- Using Degradation Measures to Estimate a Time-to-Failure Distribution
- Models for Variable-Stress Accelerated Life Testing Experiments Based on Wiener Processes and the Inverse Gaussian Distribution
This page was built for publication: Remaining useful life prediction: A multiple product partition approach