References
- Aitken, M. (1987) “Modeling Variance Heterogeneity in Normal Regression Using GLIM”. Applied Statistics 36, pp. 332–339.
- Box, G. E. P. and Draper, N. R. (1959). “A Basis for the Selection of a Response Surface Design”. Journal of the American Statistical Association 54, pp. 622–652.
- Box, G. E. P. and Draper, N. R. (1963). “The Choice of a Second-Order Rotatable Design”. Biometrika 50, pp. 335–352.
- Box, G. E. P. and Meyer, R. D. (1986). “Dispersion Effects from Fractional Designs”. Technometrics 28, pp. 19–27.
- Box, G. E. P. and Wilson, K. B. (1951). “On the Experimental Attainment of Optimum Conditions”. Journal of the Royal Statistical Society B 13, pp. 1–38.
- Cook, R. D. and Weisberg, S. (1983). “Diagnostics for Heteroscedasticity in Regression”. Biometrika 70, pp. 1–10.
- Davidian, M. and Carroll, R. J. (1987). Transformation and Weighting in Regression. Chapman & Hall, New York, NY.
- Kiefer, J. (1959). “Optimum Experimental Designs”. Journal of the Royal Statistical Society B 21, pp. 272–319.
- Kiefer, J. and Wolfowitz, J. (1959). “Optimum Designs in Regression Problems”. Annals of Mathematical Statistics, 30, pp. 271–294.
- Mays, D. and Easter, S. (1997). “Optimal Response Surface Designs in the Presence of Dispersion Effects”. Journal of Quality Technology 29, pp. 59–70.
- McCullagh, P. and Pregibon, D. (1987). “k-Statistics and Dispersion Effects in Regression”. The Annals of Statistics 15, pp. 202–219.
- Myers, R. H. and Montgomery, D. C. (1995). Response Surface Methodology: Process and Product Optimization Using Designed Experiments. John Wiley & Sons, New York, NY.
- Nair, V. N. and Pregibon, D. (1988). “Analyzing Dispersion Effects From Replicated Factorial Experiments”. Technometrics 30, pp. 247–257.
- Pukelsheim, F. (1993). Optimal Design of Experiments. John Wiley & Sons, New York, NY.
- Sas Institute, Inc. (1985). SAS/IML User's Guide, Ver. 5. SAS Institute, Cary, NC.
- Taguchi, G. (1977). Experimental Design, Vols. 1 & 2. Maruzen, Tokyo, Japan.
- Taguchi, G. (1986). Introduction to Quality Engineering. Asian Productivity Organization, Tokyo, Japan.
- Taguchi, G. (1988). SN-Ratio for the Quality Evaluation. Japanese Standards Association, Tokyo, Japan.
- Taguchi, G. and Wu, Y. (1980). Introduction to Off-Line Quality Control”. Central Japan Quality Control Association, Nagoya, Japan.
- Vining, G. G. and Schaub, D. (1996). “Experimental Designs for Estimating Both Mean and Variance Functions”. Journal of Quality Technology 28, pp. 135–147.
- Yates, F. (1937). The Design and Analysis of Factorial Experiments. Imperial Bureau of Soil Science, London, UK.