D- And A- Optimal Orthogonally Blocked Mixture Component-Amount Designs via Projections

  • Bushra Husain Aligarh Muslim University
  • Afrah Hafeez
Keywords: Additive quadratic mixture amount model, Reduced cubic mixture amount model, D-optimality, A-optimality, Latin squares, Mixture experiments.

Abstract

Mixture experiments are usually designed to study the effects on the response by changing the relative proportions of the mixture ingredients. This is usually achieved by keeping the total amount fixed but in many practical applications such as medicine or biology, not only are the proportions of mixture ingredients involved but also their total amount is of particular interest. Such experiments are called mixture amount experiments. In such experiments, the usual constraint on the mixture proportions that they should sum to unity is relaxed. The optimality of the design strictly depends on the nature of the underlying model. In this paper, we have obtained D- and A- optimal orthogonally blocked mixture component-amount designs in two and three ingredients via projections based on the reduced cubic canonical model presented by Husain and Sharma [7] and the additive quadratic mixture model proposed by Husain and Parveen [3], respectively.

Author Biography

Bushra Husain, Aligarh Muslim University
Working as Assistant Professor  (Stage -III) in Statistics at Women's College, A. M. U. Cleared the joint CSIR- UGC JRF and Eligibility for Lectureship NET held in June, 2002. M. Phil Dissertation on Design of Experiments entitled "Fractional Factorial Designs: A Review" from University of Delhi in 2002. Awarded Ph. D entitled "Optimal orthogonally blocked mixture designs using F-squares" from University of Delhi in 2012. Author of ten research papers published in Communications in Statistics - Simulation and Computation (Taylor and Francis), Metron, Statistics and Applications, Statistics (Taylor and Francis), Journal of the Korean Statistical Society (Elsevier), Int. J. Expt. Design and Process Optimisation (Inderscience), Journal of the Indian Society for Probability and Statistics (Springer) and Advanced Modeling and Optimization. Current profile includes teaching and research guidance. Supervised one M. Phil and one Ph. D Scholar and is presently guiding two Ph. D Scholars in the field of Design of Experiments. Life member of Indian Science Congress Association, Indian Society for Probability and Statistics, Indian Society of Agricultural Statistics and Society of Statistics, Computer and Applications.

References

M. L. Aggarwal, P. Singh, V. Sarin, and B. Husain, Orthogonally blocked mixture component-amount designs

via projections of F-squares, Journal of the Korean Statistical Society, vol. 41, no. 1, pp. 49-60, 2012.

B. Husain, and A. Hafeez, Optimal and nearly optimal orthogonally blocked designs for an additive quadratic

mixture model in three components, Advanced Modeling and Optimization, vol. 18. no. 2, pp. 249-264, 2016.

B. Husain, and S. Parveen, F- square based four components D-, A-, and E- optimal orthogonal designs for an

additive quadratic mixture model, Journal of the Indian Society for Probability and Statistics, vol. 17, pp. 95-109,

B. Husain, and S. Parveen, Four component F- square based nearly D- and A-optimal orthogonal block designs

for additive quadratic mixture model and reduced cubic canonical model, Aligarh Journal of Statistics, vol. 38, pp.

-161, 2018.

B. Husain, and S. Parveen, Orthogonal blocks of two and three mixture component amount blends via

projections of F- squares based design, International Journal of Statistics and Reliability Engineering, vol 7(1),

pp. 22-40, 2020.

B. Husain, and S. Sharma, Uniform designs based on F squares, Int. J. of Experimental Design and Process

Optimisation, vol. 5, no. 1/2, pp. 53-67, 2016.

B. Husain, and S. Sharma, F squares based optimal designs for reduced cubic canonical models in four

components, Int. J. of Experimental Design and Process Optimisation, vol. 5, no. 3, pp. 206-221, 2017.

B. Husain, and S. Sharma, F squares based efficient uniform designs for mixture experiments in three and four

components, Aligarh Journal of Statistics, vol. 39, pp. 53-74, 2019.

P. W. M. John, Experiments with mixture involving process variables, Technical report 8, Center for Statistical

Sciences, University of Texas, Austin, TX, pp. 1-17, 1984.

G. F. Piepel, A note on models for mixture-amount experiments when the total amount takes a zero value,

Technometrics, vol. 30, pp. 49-50, 1988.

G. F. Piepel, and J.A. Cornell, Models for mixture experiments when the response depends on the total amount,

Technometrics, vol. 27, pp. 219-227, 1985.

P. Prescott, and N. R. Draper, Mixture component-amount designs via projections including orthogonally

blocked designs, Journal of Quality Technology, vol. 36, no. 4, pp. 413-431, 2004.

Published
2023-01-18
How to Cite
Husain, B., & Hafeez, A. (2023). D- And A- Optimal Orthogonally Blocked Mixture Component-Amount Designs via Projections. Statistics, Optimization & Information Computing, 11(3), 655-669. https://doi.org/10.19139/soic-2310-5070-591
Section
Research Articles