Objective Bayesian Analysis for Linear Degradation Models

References

• Bae , S. J. , Kvam , P. H. ( 2004 ). A nonlinear random coefficients model for degradation testing . Technometrics 46 : 460 – 469 .
   Web of Science ®Google Scholar
• Berger , J. O. , Bernardo , J. M. ( 1989 ). Estimating a product of means: Bayesian analysis with reference priors . J. Amer. Statist. Assoc. 84 : 200 – 207 .
   Web of Science ®Google Scholar
• Berger , J. O. , Bernardo , J. M. ( 1992 ). On the development of reference priors (Disc: pp. 49–60). Bayesian Statistics 4. Proc. Fourth Valencia Int. Meeting, Wenzhou, China, pp. 35–49 .
   Google Scholar
• Berger , J. O. , Oliveira , V. , Sanso , B. ( 2001 ). Objective bayesian analysis of spatially correlated data . J. Amer. Statist. Assoc. 96 : 1361 – 1374 .
   Web of Science ®Google Scholar
• Bernardo , J. M. ( 1979 ). Reference posterior distributions for Bayesian inference (C/R pp. 128–147) . J. Roy. Statist. Soc. Ser. B, Methodol. 41 : 113 – 128 .
   Google Scholar
• Datta , G. S. , Sweeting , T. J. ( 2005 ). Probability matching priors . In: Dey , D. K. , Rao , C. R. , eds. Handbook of Statistics 25. Bayesian Thinking: Modeling and Computation . Amsterdam : North-Holland , pp. 91 – 114 .
   Google Scholar
• Doksum , K. A. , Hoyland , A. ( 1992 ). Model for variable-stress accelerated life testing experiments based on wiener processes and the inverse gaussian distribution . Technometrics 34 : 74 – 82 .
   Web of Science ®Google Scholar
• Jeffreys , H. ( 1961 ). Theory of Probability. , 3rd ed. Oxford : Oxford University Press .
   Google Scholar
• Lu , C. J. , Meeker , W. Q. ( 1993 ). Using degradation measures to estimate a time-to-failure distribution . Technometrics 35 : 161 – 174 .
   Web of Science ®Google Scholar
• Lu , C. J. , Park , J. , Yang , Q. ( 1997 ). Statistical inference of a time-to-failure distribution derived from linear degradation data . Technometrics 39 : 391 – 400 .
   Web of Science ®Google Scholar
• Meeker , W. Q. , Escobar , L. A. ( 1998 ). Statistical Methods for Reliability Data . New York : John Wiley and Sons .
   Google Scholar
• Nelson , W. ( 1990 ). Accelerated Testing: Statistical Models, Test Plans, and Data Analysis . New York : John Wiley and Sons .
   Google Scholar
• Peng , C. Y. , Tseng , S. T. ( 2009 ). Mis-specification analysis of linear degradation models . IEEE Trans. Reliab. 58 : 444 – 455 .
   Web of Science ®Google Scholar
• Pettit , L. I. , Young , K. D. S. ( 1999 ). Bayesian analysis of inverse gaussian lifetimes with measures of degradation . J. Statist. Computat. Simul. 63 : 217 – 234 .
   Web of Science ®Google Scholar
• Robinson , M. E. , Crowder , M. J. ( 2000 ). Bayesian methods for a growthcure degradation model with repeated measures . Lifetime Data Anal. 6 : 357 – 374 .
   PubMed Web of Science ®Google Scholar
• Takeda , E. , Suzuki , N. ( 1983 ). An empirical model for device degradation due to hot-carrier injection . IEEE Electron Dev. Lett. 4 : 111 – 113 .
   Web of Science ®Google Scholar
• Tseng , S. T. , Tang , J. , Ku , I. H. ( 2003 ). Determination of burn-in parameters and residuals life of highly reliable products . Naval Res. Logist. 50 : 1 – 14 .
   Web of Science ®Google Scholar
• Wu , S. J. , Shao , J. ( 1999 ). Beliability analysis using the least squares method in nonlinear mixed-effect degradation models . Statistica Sinica 9 : 855 – 877 .
   Web of Science ®Google Scholar
• Yu , H. F. , Tseng , S. T. ( 2002 ). Designing a screening experiment for highly reliable products . Naval Res. Logist. 49 : 514 – 526 .
   Web of Science ®Google Scholar