References
- Casella, G., and E. I. George. 1992. Explaining the Gibbs sampler. The American Statistician 46: 167–174.
- Chib, S., and E. Greenberg. 1995. Understanding the Metropolis Hastings algorithm. The American Statistician 49:327–335.
- Gelman, A., J. B. Carlin, H. S. Stern, D. B. Dunson, A. Vehtari, and D. B. Rubin. 2013. Bayesian data analysis, 3rd ed. Boca Raton, FL: Chapman and Hall.
- Hamada, M. S. 2005. Using degradation data to assess reliability. Quality Engineering 17: 615–620.
- Hastie, T., R. Tibshirani, and R. Friedman. 2009. The elements of statistical learning, 2nd ed. New York: Springer.
- Lu, C. J., and W. Q. Meeker. 1993. Using degradation measurements to estimate a time-to-failure distribution. Technometrics 35: 161–174.
- O’Malley, A. J., and A. M. Zaslavsky. 2008. Domain-level covariance analysis for multilevel survey data with structured nonresponse. Journal of the American Statistical Association 103: 1405–1418.
- R Core Team. 2016. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. http://www.R-project.org (accessed October 31, 2016).
- Shiau, J. H., and H. Lin. 1999. Analyzing accelerated degradation data by nonparametric regression. IEEE Transactions on Reliability 48: 149–158.
- Spiegelhalter, D., A. Thomas, N. Best, and D. Lunn. 2010. WinBUGS Version 1.4.3 User Manual. https://www.mrc-bsu.cam.ac.uk/software/bugs/the-bugs-project-winbugs/ (accessed May 9, 2017).
- Weaver, B. P., and M. S. Hamada. 2016. Quality quandaries: a gentle introduction to Bayesian statistics. Quality Engineering 28: 508–514.
- Xie, Y., C. B. King, Y. Hong, and Q. Yang. 2015. Semi-parametric models for accelerated destructive degradation test data analysis. Preprint. arXiv:1512.03036.