Robust estimation of complicated profiles using wavelets

References

• Abdel-Salam, A.S.G. (2009). Profile monitoring with fixed and random effects using nonparametric and semiparametric methods. Doctoral dissertation. Virginia Polytechnic Institute and State University.
   Google Scholar
• Abdel-Salam, G.A., Birch, J.B., Jensen, W.A. (2013). A semiparametric mixed model approach to phase I profile monitoring. Qual Reliab Eng Int. 29:555–569.
   Web of Science ®Google Scholar
• Bakshi, B.R. (1999). Multiscale analysis and modeling using wavelets. J Chemom. 13(3--4):415–434.
   Web of Science ®Google Scholar
• Chen, Y., Birch, J.B., Woodall, W.H. (2014). Cluster-based profile monitoring in phase I analysis. J Qual Technol. To appear.
   Google Scholar
• Chicken, E., Pignatiello, J.J., Simpson, J.R. (2009). Statistical process monitoring of non-linear profiles using wavelets. J Qual Technol. 41:198–212.
   Web of Science ®Google Scholar
• Croux, C., Gazen, A.R. (2005). High breakdown estimators for principal components: the projection pursuit approach revisited. J Multivariate Anal. 95(1):206–226.
   Web of Science ®Google Scholar
• Ding, Y., Zeng, L., Zhou, S. (2006). Phase I analysis for monitoring nonlinear profiles in manufacturing processes. J Qual Technol. 38(3):199–216.
   Web of Science ®Google Scholar
• Donoho, D.L. (1982). Breakdown properties of multivariate location estimators. Ph.D. Qualifying Paper, Harvard University.
   Google Scholar
• Ganeson, R., Das, T.K., Sikder, A.K., Kumar, A. (2002). A functional data analytic approach to signal discrimination. Technometrics. 43(1):1–9.
   Web of Science ®Google Scholar
• Gardner, M.M., Lu, J.C., Gyurcsik, R.S., Davis, J.C., Mozumder, P.K. (1997). Equipment fault detection using spatial signatures. IEEE Trans. Compon Packing Manuf Technol. 20:295–303.
   Google Scholar
• Hamerly, G., Elkan, C. (2003). Learning the k in k-Means. In proceeding of seventeenth Annual Conference of Neural Information Processing Systems (NIPS), British Columbia, Canada, December 8--13, 2003, pp. 281–288.
   Google Scholar
• Huber, P.J. (1985). Projection pursuit. Ann. Stat. 13:435–475.
   Web of Science ®Google Scholar
• Jeong, M.K., Lu, J.C. (2006). Wavelets based SPC procedure for complicated functional data. Int J Prod Res. 44(4):729–744.
   Web of Science ®Google Scholar
• Kang, L., Albin, S.L. (2000). On-line monitoring when the process yields linear profile. J Qual Technol. 32:418–426.
   Web of Science ®Google Scholar
• Kim, K., Mahmoud, M.A., Woodall, W.H. (2003). On the monitoring of linear profiles. J Qual Technol. 35:317–328.
   Web of Science ®Google Scholar
• Klawonn, F., Hoppner, F. (2009). Fuzzy clustering analysis from the viewpoint of robust statistics. Stud. Fuzziness Soft Comput. 243:439–455.
   Google Scholar
• Mahmoud, M.A., Parker, P.A., Woodall, W.H., Hawkins, D.M. (2007). A change point method for linear profile data. Qual Reliab Eng Int. 23(2):247–268.
   Web of Science ®Google Scholar
• Maronna, R.A., Martin, R.D., Yohai, V.J. (2006). Robust Statistics: Theory and Methods. New York: John Wiley and Sons.
   Google Scholar
• Mestek, O., Pavlik, J., Suchanek, M. (1994). Multivariate control charts: Control charts for calibration curves. Fresenius Journal of Analytical Chemistry 350(6):344--351.
   Google Scholar
• Noorossana, R., Saghaei, A., Amiri, A. (2011). Statistical Analysis of Profile Monitoring. New Jersey: John Wiley and Sons.
   Google Scholar
• Ogden, R.T. (1997). Essential Wavelets for Statistical Applications and Data Analysis. Boston: Birkhauser.
   Google Scholar
• Paynabar, K., Jin, J. (2011). Characterization of nonlinear profiles variations using mixed-effect models and wavelets. IIE Trans. 43:275–290.
   Web of Science ®Google Scholar
• Rock, D.M., Woodruff, D.L. (1993). Computation of robust estimators of multivariate location and shape. Stat Neerl. 47(1):27–42.
   Google Scholar
• Rousseeuw, P.J. (1985). Multivariate estimation with high breakdown point. Math Stat Appl. 8:283--297.
   Google Scholar
• Rousseeuw, P.J., Leroy, A.M. (1987). Robust Regression and Outlier Detection. New York: John Wiley and Sons.
   Google Scholar
• Rousseeuw, P., Yohai, V. (1984). Robust regression by means of S-estimators. In Robust and nonlinear time series analysis. (pp. 256--272). Springer US.
   Google Scholar
• Stahel, W.A. (1981). Robust schatzungen: Infinitestimale optimalitatund und schatzungen von kovariazmatrizen. Ph.D. diss. ETH Zurich.
   Google Scholar
• Stover, F.S., Brill, R.V. (1998). Statistical quality control applied to ion chromatography calibrations. J Chromatogr. 804:37–43.
   Web of Science ®Google Scholar
• Sugar, C.A., James, G.M. (2003). Finding the numbers of clusters in a dataset. J Am Stat Assoc. 98(463):750–763.
   Web of Science ®Google Scholar
• Sullivan, J.H. (2002). Detection of multiple change points from clustering individual observations. J Qual Technol. 34(4):371–383.
   Web of Science ®Google Scholar
• Walker, E., Wright, S.P. (2002). Comparing curves using additive models. J Qual Technol. 34(1):118–129.
   Web of Science ®Google Scholar
• Wasserman, L. (2006). All of Non Parametric Statistics. New York: Springer.
   Google Scholar
• Woodall, W.H., Spitzer, D.J., Montgomery, D.C., Gupta, S. (2004). Using control charts to monitor process and product quality profiles. J Qual Technol. 36(3):309–320.
   Web of Science ®Google Scholar
• Wu, K.L., Yang, M.S. (2002). Alternative C-Means clustering algorithm. Pattern Recognit. 35:2267–2278.
   Web of Science ®Google Scholar
• Zhang, H., Albin, S. (2009). Detecting outliers in complex profiles using a x2 control chart method. IIE Trans. 41(4):335–345.
   Web of Science ®Google Scholar
• Zhou, C., Zhang, Y., Wang, Z. (2006). A control chart based on a change point model for monitoring linear profiles. IIE Trans. 38(12):1093–1103.
   Web of Science ®Google Scholar