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Original Article

Calculating confidence intervals for percentiles of accelerated life tests with subsampling

, , , & ORCID Icon
Pages 424-438 | Accepted 02 Mar 2018, Published online: 20 Mar 2018

References

  • Fan, T. H., Hsu, T. M., & Peng, K. J. (2013). Bayesian inference of a series system on Weibull step-stress accelerated life tests with dependent masking. Quality technology & quantitative management, 10, 291–303.
  • Freeman, L. J. (2011). A cautionary tale: Small sample size concerns for grouped lifetime data. Quality Engineering, 23, 134–141.
  • Freeman, L. J., & Vining, G. G. (2010). Reliability data analysis for life test experiments with subsampling. Journal of Quality Technology, 42, 233–241.
  • Freeman, L. J., & Vining, G. G. (2013). Reliability data analysis for life test designed experiments with sub-sampling. Quality and Reliability Engineering International, 29, 509–519.
  • Kensler, J. L., Freeman, L. J., & Vining, G. G. (2014). A practitioner’s guide to analysing reliability experiments with random blocks and subsampling. Quality Engineering, 26, 359–369.
  • Kensler, J. L., Freeman, L. J., & Vining, G. G. (2015). Analyzing reliability experiments with random blocks and subsampling. Journal of Quality Technology, 47, 235–251.
  • Lawless, J. F. (1982). Statistical models and methods for lifetime data. New York, NY: John Wiley & Sons.
  • Lewis, S. L., Montgomery, D. C., & Myers, R. H. (2001). Examples of designed experiments with non-normal responses. Journal of Quality Technology, 33, 265–278.
  • Li, M., & Meeker, W. Q. (2014). Application of Bayesian methods in reliability data analyses. Journal of Quality Technology, 46, 1–23.
  • Liu, X., & Tang, L. C. (2013). Analysis of reliability experiments with blocking. Quality Technology and Quantitative Management, 10, 141–160.
  • Lv, S. S., Niu, Z. W., Qu, L., He, S. G., & He, Z. (2015). Reliability modeling of accelerated life tests with both random effects and nonconstant shape parameters. Quality Engineering, 27, 329–340.
  • Lv, S. S., Niu, Z. W., Wang, G. D., Qu, L., & He, Z. (2017). Lower percentile estimation of accelerated life tests with nonconstant scale parameter. Quality and Reliability Engineering International, 33, 1437–1446.
  • Meeker, W. Q., & Escobar, L. A. (1998). Statistical methods for reliability data. New York, NY: John Wiley & Sons.
  • Morita, L. H. M., Tomazella, V. L. D., & Louzada, F. (2018). Accelerated lifetime modelling with frailty in a non-homogeneous Poisson Process for analysis of recurrent events data. Quality Technology & Quantitative Management, 15, 209–229. doi:10.1080/16843703.2016.1208936
  • Mueller, G., & Rigdon, S. E. (2015). The constant shape parameter assumption in Weibull regression. Quality Engineering, 27, 374–392.
  • Nelson, W. B. (1990). Accelerated testing: Statistical Models, test plans and data analysis. Hoboken, NJ: John Wiley & Sons.
  • Pan, R., & Kozakai, Y. (2013). Semiparametric model and Bayesian analysis for clustered accelerated life testing data. Statistical Research Letters, 2, 1–11.
  • Seo, K., & Pan, R. (2016). Data analysis for accelerated life tests with constrained randomization. IEEE Annual Reliability and Maintainability Symposium (RAMS), Tucson, AZ, doi:10.1109/RAMS.2016.7447962
  • Seo, K., & Pan, R. (2017). Data analysis of step-stress accelerated life tests with heterogeneous group effects. IISE Transactions, 49, 885–898.
  • Thoman, D. R., Bain, L. J., & Antle, C. E. (1969). Inferences on the parameters of the Weibull distribution. Technometrics, 11, 445–460.
  • Vining, G. G. (2013). Technical advice: Experimental protocol and the basic principles of experimental design. Quality Engineering, 25, 307–311.
  • Vining, G. G., Freeman, L. J., & Kensler, J. L. (2015). An overview of designing experiments for reliability data. In Frontiers in Statistical Quality Control, vol. 11. New York, NY: Springer International Publishing.
  • Vining, G. G., Kulahci, M., & Pedersen, S. (2016). Recent advances and future directions for quality engineering. Quality and Reliability Engineering International, 32, 863–875.
  • Wang, G. D., He, Z., Xue, L., Cui, Q. A., Lv, S. S., & Zhou, P. P. (2017). Bootstrap analysis of designed experiments for reliability improvement with a non-constant scale parameter. Reliability Engineering & System Safety, 160, 114–121.
  • Wang, G. D., Niu, Z. W., & He, Z. (2015a). Accelerated lifetime data analysis with a nonconstant shape parameter. Mathematical Problems in Engineering, 2015, 1–8.
  • Wang, G. D., Niu, Z. W., & He, Z. (2015b). Bias reduction of MLEs for the Weibull distributions under grouped data. Quality Engineering, 27, 341–352.
  • Wang, G. D., Niu, Z. W., Lv, S. S., Qu, L., & He, Z. (2016). Bootstrapping analysis of lifetime data with subsampling. Quality and Reliability Engineering International, 32, 1945–1953.
  • Yang, Z., & Lin, D. K. (2007). Improved maximum-likelihood estimation for the common shape parameter of several Weibull populations. Applied Stochastic Models in Business and Industry, 23, 373–383.
  • Yuan, M., Hong, Y., Escobar, L. A., & Meeker, W. Q. (2018). Two-sided tolerance intervals for members of the (log)-location-scale family of distributions. Quality Technology & Quantitative Management. 15, 374–392. doi:10.1080/16843703.2016.1226594
  • Zelen, M. (1959). Factorial experiments in life testing. Technometrics, 1, 269–288.

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