Robust designs for multinomial models

References

• Adewale, A. J., and D. P. Wiens. 2009. Robust designs for misspecified logistic models. Journal of Statistical Planning and Inference 139:3–15.
   Web of Science ®Google Scholar
• Adewale, A. J., and X. Xu. 2010. Robust designs for generalized linear models with possible overdispersion and misspecified link functions. Computational Statistics and Data Analysis 54:875–890.
   Web of Science ®Google Scholar
• Aranda-Ordaz, F. J. 1981. On two families of transformations to additivity for binary response data. Biometrika 61:357–363.
   Web of Science ®Google Scholar
• Czado, C. 1989. Link misspecification and data selected transformations in binary regression models. Technical report, Ph.D. Thesis. School of Operations Research and Industrial Engineering, Cornell University, Ithaca, NY.
   Google Scholar
• Czado, C. 1992. On link selection in generalized linear models. In Lecture Notes in Statistics, ed. L. Fahrmeir, B. Francis, R. Gilchrist, and G. Tutz, Volume 78, pp. 60–65, New York, NY: Springer.
   Google Scholar
• Czado, C. 1993. Fitting generalized linear models with parametric link in S. Technical Report 93-26, Department of Mathematics and Statistics, York University, North York, Canada.
   Google Scholar
• Czado, C. 1997. On selecting parametric link transformation families in generalized linear models. Journal of Statistical Planning and Inference 61:125–139.
   Web of Science ®Google Scholar
• Czado, C., and T. J. Santner. 1992. The effect of link misspecification on binary regression analysis. Journal of Statistical Planning and Inference 33:213–231.
   Web of Science ®Google Scholar
• Das, I., M. Aggarwal, and S. Mukhopadhyay. 2015. Robust designs in generalized linear models: A quantile dispersion graphs approach. Communications in Statistics-Simulation and Computation 44 (9):2348–2370.
   Web of Science ®Google Scholar
• Das, I., and S. Mukhopadhyay. 2014. On generalized multinomial models and joint percentile estimation. Journal of Statistical Planning and Inference 145:190–203.
   Web of Science ®Google Scholar
• Fahrmeir, L., and G. Tutz. 2001. Multivariate Statistical Modelling Based on Generalized Linear Models. 2nd ed. New York: Springer.
   Google Scholar
• Gennings, C., W. H. Jr. Carter, and B. R. Martin. 1994. Drug interactions between morphine and marijuana. In Case Studies in Biometry, ed. N. Lange, L. Ryan, L. Billard, D. Brillinger, L. Conquest, and J. Greenhouse, pp. 429–451, New York: Wiley.
   Google Scholar
• Guerrero, V., and R. Johnson. 1982. Use of the Box Cox transformation with binary response models. Biometrika 69:309–314.
   Web of Science ®Google Scholar
• Huyer, W., and A. Neumaier. 1999. Global optimization by multilevel coordinate search. Journal of Global Optimization 14:331–355.
   Web of Science ®Google Scholar
• Lang, J. B. 1999. Bayesian ordinal and binary regression models with a parametric family of mixture links. Computational Statistics and Data Analysis 31:59–87.
   Web of Science ®Google Scholar
• Lophaven, S. N., H. B. Nielsen, and J. Sondergaard. 2002. A MATLAB kriging toolbox. Technical report, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark.
   Google Scholar
• MATLAB. 2017. version 9.3.0.713579 (R2017b). Natick, MA: The MathWorks Inc.
   Google Scholar
• Mukhopadhyay, S., and A. I. Khuri. 2008. Comparison of designs for multivariate generalized linear models. Journal of Statistical Planning and Inference 138:169–183.
   Web of Science ®Google Scholar
• Mukhopadhyay, S., and A. I. Khuri. 2012. Comparison of designs for generalized linear models under model misspecification. Statistical Methodology 9:285–304.
   Google Scholar
• Pregibon, D. 1980. Goodness of link tests for generalized linear models. Journal of the Royal Statistical Society 29:15–24.
   Google Scholar
• Prentice, R. L. 1975. Discrimination among some parametric models. Biometrika 64:607–614.
   Google Scholar
• Prentice, R. L. 1976. A generalization of the probit and logit methods for dose response curves. Biometrics 32:761–768.
   PubMed Web of Science ®Google Scholar
• Santner, T. J., B. J. Williams, and W. I. Notz. 2013. The design and analysis of computer experiments. New York, NY: Springer Science & Business Media.
   Google Scholar
• Stukel, T. A. 1988. Generalized logistic models. Journal of the American Statistical Association 83:426–431.
   Web of Science ®Google Scholar
• Taylor, J. M. G. 1988. The cost of generalized logistic regression. Journal of the American Statistical Association 83:1078–1083.
   Web of Science ®Google Scholar
• Wald, A. 1943. Tests of statistical hypotheses concerning several parameters when the number of observations is large. Transactions of the American Mathematical Society 54:426–482.
   Google Scholar
• Woods, D. C., S. M. Lewis, J. A. Eccleston, and K. G. Russell. 2006. Designs for generalized linear models with several variables and model uncertainty. Technometrics 48:284–292.
   Web of Science ®Google Scholar