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A class of composite designs for response surface methodology

Author

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  • Georgiou, Stelios D.
  • Stylianou, Stella
  • Aggarwal, Manohar

Abstract

A class of efficient and economical response surface designs that can be constructed using known designs is introduced. The proposed class of designs is a modification of the Central Composite Designs, in which the axial points of the traditional central composite design are replaced by some edge points of the hypercube that circumscribes the sphere of zero center and radius a. An algorithm for the construction of these designs is developed and applied. The constructed designs are suitable for sequential experimentation and have higherD-values than those of known composite designs. The properties of the constructed designs are further discussed and evaluated in terms of rotatability, blocking, and D-optimality under the full second-order model.

Suggested Citation

  • Georgiou, Stelios D. & Stylianou, Stella & Aggarwal, Manohar, 2014. "A class of composite designs for response surface methodology," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1124-1133.
    • Handle: RePEc:eee:csdana:v:71:y:2014:i:c:p:1124-1133
    DOI: 10.1016/j.csda.2013.03.010
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    References listed on IDEAS

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    1. Goos, P. & Donev, A.N., 2006. "Blocking response surface designs," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1075-1088, November.
    2. Trinca, L. A. & Gilmour, S. G., 2002. "Erratum to "An algorithm for arranging response surface designs in small blocks" [Comput. Statist. Data Anal. 33 (2000) 25-43]," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 475-474, September.
    3. Steven G. Gilmour, 2006. "Response Surface Designs for Experiments in Bioprocessing," Biometrics, The International Biometric Society, vol. 62(2), pages 323-331, June.
    4. Trinca, Luzia A. & Gilmour, Steven G., 2000. "An algorithm for arranging response surface designs in small blocks," Computational Statistics & Data Analysis, Elsevier, vol. 33(1), pages 25-43, March.
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    Cited by:

    1. M. Gholipour & A. T. Haghighat & M. R. Meybodi, 2018. "Congestion avoidance in cognitive wireless sensor networks using TOPSIS and response surface methodology," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(3), pages 519-537, March.
    2. Angelina Roche, 2018. "Local optimization of black-box functions with high or infinite-dimensional inputs: application to nuclear safety," Computational Statistics, Springer, vol. 33(1), pages 467-485, March.

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