Research Article
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Year 2019, Volume: 48 Issue: 2, 580 - 591, 01.04.2019

Abstract

References

  • Agresti, A., “Foundations of Linear and Generalized Linear Models”. John Wiley & Sons, Inc., Hoboken, New Jersey, 2015.
  • Atkinson, A., “DT-Optimum Designs for Model Discrimination and Parameter Estimation”. Journal of Statistical Planning and Inference, 138, 56-64, 2008.
  • Atkinson, A., Donev, A. and Tobias, R., “Optimum Experimental Designs, with SAS”. Oxford university press, New York, 2007.
  • Boyd, S. and Vandenberghe, L., “Convex Optimization”. Cambridge University Press, Cambridge, 2004.
  • Chang, F. and Heiligers, B., “E-Optimal Designs for Polynomial Regression without Intercept”. Journal of Statistical Planning and Inference, 55, 371-387, 1996.
  • Clyde, M. and Chaloner, K., “The Equivalence of Constrained and Weighted Designs in Multiple Objective Design Problems”. Journal of the American Statistical Association, 91, 1236-1244, 1996.
  • Corana, A., Marchesi, M., Martini, C. and Ridella, S., “Minimizing Multimodal Functions of Continuous Variables with the ‘Simulated Annealing’ Algorithm”. ACM Trans. Math. Software, 13, 262–280, 1987.
  • Denman, N. G., McGree, J. M., Eccleston, J. A. and Duffull, S. B., “Design of Experiments for Bivariate Binary Responses Modelled by Copula Functions”. Computational Statistics & Data Analysis, 55, 1509-1520, 2011.
  • Dette, H., “A Note on E-Optimal Designs for Weighted Polynomial Regression”. Annals of Statistics, 21, 767-771, 1993.
  • Dette, H. and Studden, W., “Geometry of E-Optimality”. Annals of Statistics, 21, 416-433, 1993.
  • Dette, H. and Haines, L., “E-optimal Designs for Linear and Nonlinear Models with two Parameters”. Biometrika, 81, 739–754, 1994.
  • Dette, H., Melas,V. and Pepelyshev, A., “Local c-optimal and E-optimal Designs for Exponential Regression Models”. AISM, 58: 407–426, 2006.
  • Dette, H. and Wong, W.K., “E-optimal designs for the Michaelis Menten Model”. Statistics &Probability Letters, 44, 405–408, 1999.
  • Ehrenfeld, E., “On the Efficiency of Experimental Design”. Annals of Mathematical Statistics, 26, 247–255, 1955.
  • Heiligers, B., "Computing E–Optimal Polynomial Regression Designs”. Journal of Statistical Planning and Inference, 55, 219–233, 1996.
  • Heiligers, B., "E–Optimal Designs for Polynomial Spline Regression”. Journal of Statistical Planning and Inference, 75, 159-172, 1998.
  • Kilany, N. M., “Optimal Designs for Probability-based Optimality, Parameter Estimation and Model Discrimination”. Journal of the Egyptian Mathematical Society, 25, 212- 215, 2017.
  • Kilany, N. M. and Hassanein, W. A., “AP- Optimum Designs for Minimizing the Average Variance and Probability-Based Optimality”. REVSTAT – Statistical Journal, In Press, 2017.
  • Mcgree, J. M. and Eccleston, J. A., “Probability-Based Optimal Design”. Australian and New Zealand Journal of Statistics, 50 (1), 13- 28, 2008.
  • McGree, J. M., Duffull, S. B. and Eccleston, J. A., “Compound Optimal Design Criteria for Nonlinear Models”. Journal of Biopharmaceutical Statistics, 18, 646-661, 2008.
  • Mwan, D. M., Kosgei, M. K. and Rambaei, S. K., “DT- optimality Criteria for Second Order Rotatable Designs Constructed Using Balanced Incomplete Block Design”. British Journal of Mathematics & Computer Science, 22(6), 1-7, 2017.
  • Pukelsheim, F. and Studden, W., “E-Optimal Designs for Polynomial Regression”. Annals of Statistics, 21, 402-415, 1993.
  • Wald, A., “On the Efficient Design of Statistical Investigation”. Annals of Mathematical Statistics, 14, 134–140, 1943.

DE- and EDP$_{M}$- compound optimality for the information and probability-based criteria

Year 2019, Volume: 48 Issue: 2, 580 - 591, 01.04.2019

Abstract

Several optimality criteria have been considered in the literature as information-based criteria. The probability- based criteria have been recently proposed for maximizing the probability of a desired outcome. However, designs that are optimal for the information- based criteria may be inadequate for probability- based criteria. This paper introduces the DE- and EDP${}_{M}$ -- optimum designs for multi aims of optimality for Generalized Linear Models (GLMs). An equivalence theorem is proved for both compound criteria. Finally, two numerical examples are given to illustrate the potentiality of the proposed compound criteria.

References

  • Agresti, A., “Foundations of Linear and Generalized Linear Models”. John Wiley & Sons, Inc., Hoboken, New Jersey, 2015.
  • Atkinson, A., “DT-Optimum Designs for Model Discrimination and Parameter Estimation”. Journal of Statistical Planning and Inference, 138, 56-64, 2008.
  • Atkinson, A., Donev, A. and Tobias, R., “Optimum Experimental Designs, with SAS”. Oxford university press, New York, 2007.
  • Boyd, S. and Vandenberghe, L., “Convex Optimization”. Cambridge University Press, Cambridge, 2004.
  • Chang, F. and Heiligers, B., “E-Optimal Designs for Polynomial Regression without Intercept”. Journal of Statistical Planning and Inference, 55, 371-387, 1996.
  • Clyde, M. and Chaloner, K., “The Equivalence of Constrained and Weighted Designs in Multiple Objective Design Problems”. Journal of the American Statistical Association, 91, 1236-1244, 1996.
  • Corana, A., Marchesi, M., Martini, C. and Ridella, S., “Minimizing Multimodal Functions of Continuous Variables with the ‘Simulated Annealing’ Algorithm”. ACM Trans. Math. Software, 13, 262–280, 1987.
  • Denman, N. G., McGree, J. M., Eccleston, J. A. and Duffull, S. B., “Design of Experiments for Bivariate Binary Responses Modelled by Copula Functions”. Computational Statistics & Data Analysis, 55, 1509-1520, 2011.
  • Dette, H., “A Note on E-Optimal Designs for Weighted Polynomial Regression”. Annals of Statistics, 21, 767-771, 1993.
  • Dette, H. and Studden, W., “Geometry of E-Optimality”. Annals of Statistics, 21, 416-433, 1993.
  • Dette, H. and Haines, L., “E-optimal Designs for Linear and Nonlinear Models with two Parameters”. Biometrika, 81, 739–754, 1994.
  • Dette, H., Melas,V. and Pepelyshev, A., “Local c-optimal and E-optimal Designs for Exponential Regression Models”. AISM, 58: 407–426, 2006.
  • Dette, H. and Wong, W.K., “E-optimal designs for the Michaelis Menten Model”. Statistics &Probability Letters, 44, 405–408, 1999.
  • Ehrenfeld, E., “On the Efficiency of Experimental Design”. Annals of Mathematical Statistics, 26, 247–255, 1955.
  • Heiligers, B., "Computing E–Optimal Polynomial Regression Designs”. Journal of Statistical Planning and Inference, 55, 219–233, 1996.
  • Heiligers, B., "E–Optimal Designs for Polynomial Spline Regression”. Journal of Statistical Planning and Inference, 75, 159-172, 1998.
  • Kilany, N. M., “Optimal Designs for Probability-based Optimality, Parameter Estimation and Model Discrimination”. Journal of the Egyptian Mathematical Society, 25, 212- 215, 2017.
  • Kilany, N. M. and Hassanein, W. A., “AP- Optimum Designs for Minimizing the Average Variance and Probability-Based Optimality”. REVSTAT – Statistical Journal, In Press, 2017.
  • Mcgree, J. M. and Eccleston, J. A., “Probability-Based Optimal Design”. Australian and New Zealand Journal of Statistics, 50 (1), 13- 28, 2008.
  • McGree, J. M., Duffull, S. B. and Eccleston, J. A., “Compound Optimal Design Criteria for Nonlinear Models”. Journal of Biopharmaceutical Statistics, 18, 646-661, 2008.
  • Mwan, D. M., Kosgei, M. K. and Rambaei, S. K., “DT- optimality Criteria for Second Order Rotatable Designs Constructed Using Balanced Incomplete Block Design”. British Journal of Mathematics & Computer Science, 22(6), 1-7, 2017.
  • Pukelsheim, F. and Studden, W., “E-Optimal Designs for Polynomial Regression”. Annals of Statistics, 21, 402-415, 1993.
  • Wald, A., “On the Efficient Design of Statistical Investigation”. Annals of Mathematical Statistics, 14, 134–140, 1943.
There are 23 citations in total.

Details

Primary Language English
Subjects Statistics
Journal Section Statistics
Authors

W. A. Hassanein 0000-0003-4057-874X

N. M. Kilany 0000-0001-6397-6156

Publication Date April 1, 2019
Published in Issue Year 2019 Volume: 48 Issue: 2

Cite

APA Hassanein, W. A., & Kilany, N. M. (2019). DE- and EDP$_{M}$- compound optimality for the information and probability-based criteria. Hacettepe Journal of Mathematics and Statistics, 48(2), 580-591.
AMA Hassanein WA, Kilany NM. DE- and EDP$_{M}$- compound optimality for the information and probability-based criteria. Hacettepe Journal of Mathematics and Statistics. April 2019;48(2):580-591.
Chicago Hassanein, W. A., and N. M. Kilany. “DE- and EDP$_{M}$- Compound Optimality for the Information and Probability-Based Criteria”. Hacettepe Journal of Mathematics and Statistics 48, no. 2 (April 2019): 580-91.
EndNote Hassanein WA, Kilany NM (April 1, 2019) DE- and EDP$_{M}$- compound optimality for the information and probability-based criteria. Hacettepe Journal of Mathematics and Statistics 48 2 580–591.
IEEE W. A. Hassanein and N. M. Kilany, “DE- and EDP$_{M}$- compound optimality for the information and probability-based criteria”, Hacettepe Journal of Mathematics and Statistics, vol. 48, no. 2, pp. 580–591, 2019.
ISNAD Hassanein, W. A. - Kilany, N. M. “DE- and EDP$_{M}$- Compound Optimality for the Information and Probability-Based Criteria”. Hacettepe Journal of Mathematics and Statistics 48/2 (April 2019), 580-591.
JAMA Hassanein WA, Kilany NM. DE- and EDP$_{M}$- compound optimality for the information and probability-based criteria. Hacettepe Journal of Mathematics and Statistics. 2019;48:580–591.
MLA Hassanein, W. A. and N. M. Kilany. “DE- and EDP$_{M}$- Compound Optimality for the Information and Probability-Based Criteria”. Hacettepe Journal of Mathematics and Statistics, vol. 48, no. 2, 2019, pp. 580-91.
Vancouver Hassanein WA, Kilany NM. DE- and EDP$_{M}$- compound optimality for the information and probability-based criteria. Hacettepe Journal of Mathematics and Statistics. 2019;48(2):580-91.