Publication Cover
Journal of Quality Technology
A Quarterly Journal of Methods, Applications and Related Topics
Volume 35, 2003 - Issue 1
87
Views
57
CrossRef citations to date
0
Altmetric
Articles

Robust Design via Generalized Linear Models

&
Pages 2-12 | Published online: 16 Feb 2018

References

  • Box, G. E. P. (1988). “Signal-to-Noise Ratios, Performance Criteria, and Transformations (with discussion)”. Technometrics 30, pp. 1–40.
  • Box, G. E. P. and Draper, N. R. (1987). Empirical Model-Building and Response Surfaces. John Wiley, New York, NY.
  • Breslow, N. E. (1984). “Extra-Poisson Variation in Log-Linear Models”. Applied Statistics 33, pp. 38–44.
  • Carroll, R. J. and Ruppert, D. (1982). “A Comparison Between Maximum Likelihood and Generalized Least Squares in a Heteroscedastic Linear Model”. Journal of American Statistical Association 77, pp. 878–882.
  • Davidian, M. and Carroll, R. J. (1988). “A Note on Extended-Quasi-Likelihood”. Journal of Royal Statistical Society B 50, pp. 74–82.
  • Efron, B. (1986). “Double Exponential Families and Their Use in Generalized Linear Regression”. Journal of American Statistical Association 81, pp. 709–721.
  • Engel, J. (1992). “Modelling Variation in Industrial Experiments”. Applied Statistics 41, pp. 579–593.
  • Engel, J. and Huele, A. F. (1996). “A Generalized Linear Modelling Approach to Robust Design”. Technometrics 38, pp. 365–373.
  • Grego, J. M. (1993). “Generalized Linear Models and Process Variation”. Journal of Quality Technology 25, pp. 288–295.
  • Hamada, M. and Nelder, J. A. (1997). “Generalized Linear Models for Quality-Improvement Experiments”. Journal of Quality Technology 29, pp. 292–304.
  • Lane, P. W. and Nelder, J. A. (1982). “Analysis of Covariance and Standardardization as Instances of Prediction”. Biometrics 38, pp. 613–621.
  • Lee, Y. and Nelder, J. A. (1998). “Generalized Linear Models for the Analysis of Quality-Improvement Experiments”. The Canadian Journal of Statistics 26, pp. 95–105.
  • Lee, Y. and Nelder, J. A. (1999). “Robustness of the Quasilikelihood Estimator”. The Canadian Journal of Statistics 27, pp. 321–327.
  • Lee, Y. and Nelder, J. A. (2000). “The Relationship Between Double Exponential Families and Extended Quasi-Likelihood Families, with Application to Modelling Geissler's Human Sex Ratio Data”. Applied Statistics 49, pp. 413–419.
  • Lee, Y. and Nelder, J. A. (2001a). “Hierarchical Generalised Linear Models: A Synthesis of Generalised Linear Models, Random Effect Models and Structured Dispersions”. Biometrika 88, pp. 987–1006.
  • Lee, Y. and Nelder, J. A. (2001b). “Modelling and Analysing Correlated Non-Normal Data”. Statistical Modelling 1, pp. 3–16.
  • Leon, R. V.; Shoemaker, A. C.; and Kackar, R. N. (1987). “Performance Measures Independent of Adjustment (with discussion)”. Technometrics 29, pp. 253–285.
  • McCullagh P. and Nelder, J. A. (1989). Generalized Linear Models 2nd ed. Chapman and Hall, London, UK.
  • Montgomery, D. C. (1999). “Experimental Design for Product and Process Design and Development (with discussion)”. The Statistician 48, pp. 159–177.
  • Myers, R. H. and Montgomery, D. C. (1995). Response Surface Methodology. John Wiley, New York, NY.
  • Myers, R. H.; Khuri, A. I.; and Vining, G. G. (1992). “Response Surface Alternatives to the Taguchi Robust Parameter Design Approach”. American Statistician 46, pp. 131–139.
  • Nair, V. N. (1992). “Taguchi's Parameter Design: A Panel Discussion”. Technometrics 30, pp. 127–161.
  • Nelder, J. A. (1994). “The Statistics of Linear Models: Back to Basics”. Statistics and Computing 4, pp. 221–234.
  • Nelder, J. A. and Lee, Y. (1991). “Generalized Linear Models for the Analysis of Taguchi-Type Experiments”. Applied Stochastic Models and Data Analysis 7, pp. 107–120.
  • Nelder, J. A. and Lee, Y. (1992). “Likelihood, Quasi-Likelihood and Pseudo-Likelihood: Some Comparisons”. Journal of Royal Statistical Society B 54, pp. 273–284.
  • Nelder, J. A. and Lee, Y. (1998). “Letter to the Editor”. Technometrics 40, pp. 168–175.
  • Nelder, J. A. and Pregibon, D. (1987). “An Extended Quasi-Likelihood Function”. Biometrika 74, pp. 221–231.
  • Nelder, J. A. and Wedderburn, R. W. M. (1972). “Generalized Linear Models”. Journal of Royal Statistical Society A 135, pp. 370–384.
  • Pierce, D. A. and Schafer, D. W. (1986). “Residuals in Generalized Linear Models”. Journal of American Statistical Association 81, pp. 977–986.
  • Schmidt, S. R. and Launsby, R. G. (1990). Understanding Industrial Designed Experiments. Air Academy Press, Colorado Springs, CO.
  • Taguchi, G. and Wu, Y. (1985). Introduction to Off-Line Quality Control. Central Japan Quality Control Association, Nagoya, Japan.
  • Vining, G. G. and Myers, R. H. (1990). “Combining Taguchi and Response Surface Philosophies: A Dual Surface Approach”. Journal of Quality Technology 22, pp. 38–45.
  • Wedderburn, R. W. M. (1974). “Quasi-likelihood Functions, Generalized Linear Models and the Gauss-Newton Method”. Biometrika 61, pp. 439–447.
  • Wolfinger, R. D. and Tobias, R. D. (1998). “Joint Estimation of Location, Dispersion, and Random Effects in Robust Design”. Technometrics 40, pp. 62–71.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.