Robust first-order rotatable lifetime improvement experimental designs

References

• O.O. Aalen, Heterogeneity in survival analysis, Stat. Med. 7 (1988), pp. 1121–1137. doi: 10.1002/sim.4780071105
   PubMed Web of Science ®Google Scholar
• O.O. Aalen, A linear regression model for the analysis of life times, Stat. Med. 8 (1989), pp. 907–925. doi: 10.1002/sim.4780080803
   PubMed Web of Science ®Google Scholar
• O.O. Aalen, Modeling heterogeneity in survival analysis by the compound poisson distribution, Ann. Appl. Probab. 2 (1992), pp. 951–972. doi: 10.1214/aoap/1177005583
   Google Scholar
• O.O. Aalen, Effects of frailty in survival analysis, Statist. Methods Med. Res. 3 (1994), pp. 227–243. doi: 10.1177/096228029400300303
   PubMedGoogle Scholar
• M. Aitkin and D. Clayton, The fitting of exponential, Weibull and extreme value distributions to complex censored survival data using GLIM, Appl. Stat. 29 (1980), pp. 156–163. doi: 10.2307/2986301
   Google Scholar
• T.W. Anderson, In Introduction to Multivariate Statistical Analysis, 2nd ed., John Wiley and Sons, New York, 1984.
   Google Scholar
• W. Bischoff, Determinant formulas with applications to designing when the observations are correlated, Ann. Inst. Statist. Math. 47 (1995), pp. 385–399. doi: 10.1007/BF00773469
   Web of Science ®Google Scholar
• W. Bischoff, On maximin designs for correlated observations, Stat. Probab. Lett. 26 (1996), pp. 357–363. doi: 10.1016/0167-7152(95)00032-1
   Web of Science ®Google Scholar
• G.E.P. Box and R.N. Draper, Response surfaces, mixtures, and ridge analysis, 2nd ed., John Wiley and Sons, New York, 2007.
   Google Scholar
• G.E.P. Box and J.S. Hunter, Multifactor experimental designs for exploring response surfaces, Ann. Math. Statist. 28 (1957), pp. 195–241. doi: 10.1214/aoms/1177707047
   Google Scholar
• S. Chatterjee and B. Price, Regression Analysis by Examples, 3rd ed., John Wiley and Sons, New York, 2000.
   Google Scholar
• L.W. Condra, Reliability Improvement of Experiments, Marcel Dekker, New York, 1993.
   Google Scholar
• R.N. Das, Robust second order rotatable designs: Part-I, Cal. Statist. Assoc. Bull. 47 (1997), pp. 199–214.
   Google Scholar
• R.N. Das, Robust second order rotatable designs: Part-III, J. Indian Soc. Agric. Stat. 56 (2003), pp. 117–130.
   Google Scholar
• R.N. Das, Construction and analysis of robust second order rotatable designs, J. Statist. theory Appl.3 (2004), pp. 325–343.
   Google Scholar
• R.N. Das, Discrepancy in classical lifetime model classes: Some illustrations, J. Qual. 20(5) (2013), pp. 521–533.
   Google Scholar
• R.N. Das and S. Huda, On D-optimal robust designs for exponential lifetime distribution, J. Statist. Theory Appl. 10(2) (2011), pp. 198–208.
   Google Scholar
• R.N. Das and Y. Lee, Log normal versus gamma models for analyzing data from quality-improvement experiments, Qual. Eng. 21(1) (2009), pp. 79–87. doi: 10.1080/08982110802317372
   Web of Science ®Google Scholar
• R.N. Das and Y. Lee, Analysis strategies for multiple responses in quality improvement experiments, Int. J. Qual. Eng. Technol. 1(4) (2010), pp. 395–409. doi: 10.1504/IJQET.2010.035585
   Google Scholar
• R.N. Das and D.K.J. Lin, On D-optimal robust first order designs for lifetime improvement experiments, J. Stat. Plan. Inference 141(12) (2011), pp. 3753–3759. doi: 10.1016/j.jspi.2011.06.011
   Web of Science ®Google Scholar
• D. Firth, Multiplicative errors: log-normal or gamma? J. R. Stat. Soc. B. 50 (1988), pp. 266–268.
   Google Scholar
• C. Gennings, V.M. Chinchilli, and W.H. Carter Jr, Response surface analysis with correlated data: A non-linear model approach, J. Amer. Stat. Assoc. 84 (1989), pp. 805–809. doi: 10.1080/01621459.1989.10478841
   Web of Science ®Google Scholar
• J. Kiefer and H.P. Wynn, Optimum balanced block and latin square designs for correlated observations, Ann. Statist. 9 (1981), pp. 737–757. doi: 10.1214/aos/1176345515
   Web of Science ®Google Scholar
• J. Kiefer and H.P. Wynn, Optimum and minimax exact treatment designs for one-dimensional autoregressive error processes, Ann. Statist. 12 (1984), pp. 431–449. doi: 10.1214/aos/1176346498
   Web of Science ®Google Scholar
• A.I. Khuri and J.A. Cornell, Responses Surfaces, Marcel Dekker, New York, 1996.
   Google Scholar
• J.F. Lawless, Statistical Models and Methods for Lifetime Data, John Wiley and Sons, New York, 1982.
   Google Scholar
• Y. Lee and J.A. Nelder, Generalized linear models for the analysis of quality improvement experiments, Can. J. Statist. 26 (1998), pp. 95–105. doi: 10.2307/3315676
   Web of Science ®Google Scholar
• Y. Lee and J.A. Nelder, Robust design via generalized linear models, J. Qual. Tech. 35 (2003), pp. 2–12.
   Web of Science ®Google Scholar
• Y. Lee, J.A. Nelder, and Y. Pawitan, Generalized Linear Models with Random Effects (Unified Analysis via H-likelihood) Chapman and Hall, London, 2006.
   Google Scholar
• A.C. Mukhopadhyay, S.B. Bagchi, and R.N. Das, Improvement of quality of a system using regression designs, Cal. Statist. Assoc. Bull. 53 (2002), pp. 225–233.
   Google Scholar
• R.H. Myers and W.H. Carter, Response surface techniques for dual response systems, Technometrics15 (1973), pp. 301–317. doi: 10.1080/00401706.1973.10489044
   Web of Science ®Google Scholar
• R.H. Myers and D.C. Montgomery, Response Surface Methodology, John Wiley and Sons, New York, 2002.
   Google Scholar
• R.H. Myers, D.C. Montgomery, and G.G. Vining, Generalized Linear Models with Applications in Engineering and the Sciences, John Wiley & Sons, New York, 2002.
   Google Scholar
• J.A. Nelder and Y. Lee, Generalized linear models for the analysis of Taguchi-type experiments, Appl. Stoch. Models Data Anal. 7 (1991), pp. 107–120. doi: 10.1002/asm.3150070110
   Google Scholar
• R.N. Panda and R.N. Das, First order rotatable designs with correlated errors, Cal. Statist. Assoc. Bull. 44 (1994), pp. 83–101.
   Google Scholar
• F. Pukelsheim, Optimal Experimental Design, John Wiley and Sons, New York, 1993.
   Google Scholar
• S.J. Press, Applied Multivariate Analysis, Holt, Rinehart and Winston, New York, 1972.
   Google Scholar
• G. Taguchi, Introduction to Quality Engineering Asian Productivity Organization, UNIPUB, White Plains, New York, 1986.
   Google Scholar
• G. Taguchi, System of Experimental Design: Engineering Methods to Optimize Quality and Minimize Cost, UNIPUB/Kraus International, White Plains, New York, 1987.
   Google Scholar
• C.F.J. Wu and M. Hamada, Experiments and Planning Analysis, and Parameter Optimization, John Wiley and Sons, New York, 2000.
   Google Scholar