參考文獻 |
[1] Berger, J. O. (1985). Statistical Decision Theory and Bayesian Analysis (Second Edition), Springer-Verlag, New York.
[2] Casella, G. (1985). An introduction to empirical Bayes data analysis. The American Statistician, 39, 83–87.
[3] Chhikara, R. S. and Folks, J. L. (1989). The Inverse Gaussian Distribution.Theory,Methodology and Applications, Marcel Dekker, New York.
[4] Carlin, B. P. and Louis, T. A. (2000). Bayes and Eempirical Bayes Methods for Data Analysis, Chapman and Hall, New York.
[5] Doksum, K. A. and Hoyland, A. (1992). Models for variable-stress accelerated life testing experiments based on Wiener process and the inverse Gaussian distribution. Technometrics, 34, 74–82.
[6] Efron, B. (1979). Bootstrap method: another look at the jacknife. Annals of Statist , 17, 1–2682.
[7] Fan, T. H. and Wang, Y. F. (2013). An empirical Bayesian forecast in the threshold stochastic volatility models. Journal of Statistical Computation and Simulation, 83, 486–500.
[8] Geman, S. and Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6, 721–741.
[9] Hong, Y., Duan, Y., Meeker, W. Q., Stanley, D. L., and Gu, X. (2014). Statistical methods for degradation data with dynamic covariates information and an application to outdoor weathering data. To appear in Technometrics, p. DOI:10.1080/00401706.2014.915891.
[10] Hu, C. H., Lee, M. Y., and Tang, J. (2015). Optimum step-stress accelerated degradation test for Wiener degradation process under constraints. European Journal of Operational Research, 241, 412–421.
[11] Jin, G., Matthews, D. E., and Zhou, Z. (2013). A Bayesian framework for on-line degradation assessment and residual life prediction of secondary batteries in spacecraft. Reliability Engineering and System Safety, 113, 7–20.
[12] Lawless, J. F. and Crowder, M. (2004). Covariates and random effects in a gamma process model with application to degradation and failure. Lifetime Data Analysis, 10, 213–227.
[13] Liao, C. M. and Tseng, S. T. (2006). Optimal design for step-stress accelerated degradation test. IEEE Transactions on Reliability, 55, 59–66.
[14] Ling, M. H., Tsui, K. L., and Balarkrishnan, N. (2015). Accelerated degradation analysis for the quality of a system based on the gamma process. IEEE Transactions on Reliability, 64, 463–472.
[15] Morris, C. N. (1983). Parametric empirical Bayes inference: theory and applications. Journal of the American Statistical Association, 78, 47–65.
[16] Morris, C. N. (1983). Natural exponential families with quadratic variance functions: statistical theory. Annals of Statistics, 11, 515–529.
[17] Meeker, W. Q. and Escobar, L. A. (1993). A review of recent research current issues in accelerated testing. International Statistical Review, 61, 147–168.
[18] Meeker, W. Q. and Escobar, L. A. (1998). Statistical Methods for Reliability Data, Wiley, New York.
[19] Nelson, W. (1990). Accelerated Testing: Statistical Models, Test Plans, and Data Analysis, John Wiley & Sons, New York.
[20] Pettit, L. I. and Young, K. D. S. (1999). Bayesian analysis for inverse Gaussian lifetime data with measures of degradation. Journal of Statistical Computation and Simulation, 63, 217–234.
[21] Padgeet, W. and Tomlinson, M. A. (2004). Inference from accelerated degradation and failure data based on Gaussian process models. Lifetime Data Analysis, 10, 191–206.
[22] Park, C. and Padgett, W. J. (2005). Accelerated degradation models for failure based on geometric Brownian motion and gamma processes. Lifetime Data Analysis, 11, 511–527.
[23] Pan, Z. and Balarkrishnan, N. (2011). Reliability modeling of degradation of products with multiple performance characteristics based on gamma processes. Reliability Engineering and System Safety, 96, 949–957.
[24] Robbins, H. (1956). An empirical Bayes approach to statistics. In Proceeding Third Berkeley Symp.Mathematical Statistics and Probability, 1, 157–164.
[25] Robinson, M. E. and Crowder, M. J. (2000). Bayesian methods for growth-curve degradation model with repeated measures. Lifetime Data Analysis, 6, 357–374.
[26] Spiegelhalter, D. J., Best, N. G., Carlin, B. P., and Linde, A. (2002). Bayesian measures of model complexity and fit. Journal of Royal Statistical Society,Series B, 64, 583–639.
[27] Tseng, S. T. and Peng, C. Y. (2004). Optimal burn-in policy by using an integrated Wiener process. IEEE Transactions on Reliability, 36, 1161–1170.
[28] Touw, A. E. (2009). Bayesian estimation of mixed Weibull distributions. Reliability Engineering and System Safety, 94, 463–473.
[29] Whitmore, G. A. (1995). Estimating degradation by a Wiener diffusion process subject to measurement error. Lifetime Data Analysis, 1, 307–319.
[30] Whitmore, G. A. and Schenkelberg, F. (1997). Modeling accelerated degradation data using Wiener diffusion with a scale transformation. Lifetime Data Analysis, 3, 27–45. |