IDEAS home Printed from https://ideas.repec.org/a/eee/ecosta/v28y2023icp138-154.html
   My bibliography  Save this article

Partially orthogonal blocked three-level response surface designs

Author

Listed:
  • Großmann, Heiko
  • Gilmour, Steven G.

Abstract

When fitting second-order response surface models in a hypercuboidal region of experimentation, the variance matrices of D-optimal continuous designs have a particularly attractive structure, as do many regular unblocked exact designs. Methods for constructing blocked exact designs which preserve this structure and are orthogonal, or nearly orthogonal, are developed. Partially orthogonal designs are built using a small irregular fraction of a two- or three-level design and a regular fractional factorial design as building blocks. Results are derived which relate the properties of the blocked design to these components. Moreover, it is shown how the designs can be augmented to ensure that the model can be fitted and a method for constructing designs with small blocks is presented. Examples illustrate that partially orthogonal designs can compete with more traditional designs in terms of both efficiency and overall size of the experiment.

Suggested Citation

  • Großmann, Heiko & Gilmour, Steven G., 2023. "Partially orthogonal blocked three-level response surface designs," Econometrics and Statistics, Elsevier, vol. 28(C), pages 138-154.
  • Handle: RePEc:eee:ecosta:v:28:y:2023:i:c:p:138-154
    DOI: 10.1016/j.ecosta.2021.08.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2452306221001015
    Download Restriction: Full text for ScienceDirect subscribers only. Contains open access articles

    File URL: https://libkey.io/10.1016/j.ecosta.2021.08.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yong-Dao Zhou & Hongquan Xu, 2017. "Composite Designs Based on Orthogonal Arrays and Definitive Screening Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1675-1683, October.
    2. Neil A. Butler, 2003. "Some theory for constructing minimum aberration fractional factorial designs," Biometrika, Biometrika Trust, vol. 90(1), pages 233-238, March.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Peng-Fei Li & Min-Qian Liu & Run-Chu Zhang, 2007. "2 m 4 1 designs with minimum aberration or weak minimum aberration," Statistical Papers, Springer, vol. 48(2), pages 235-248, April.
    3. da Silva, Marcelo A. & Gilmour, Steven G. & Trinca, Luzia A., 2017. "Factorial and response surface designs robust to missing observations," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 261-272.
    4. Kalliopi Mylona & Harrison Macharia & Peter Goos, 2013. "Three-level equivalent-estimation split-plot designs based on subset and supplementary difference set designs," IISE Transactions, Taylor & Francis Journals, vol. 45(11), pages 1153-1165.
    5. Goos, P. & Donev, A.N., 2006. "Blocking response surface designs," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1075-1088, November.
    6. Gautam, Ashish & Mondal, Monoj Kumar, 2024. "Post-combustion CO2 absorption-desorption performance of novel aqueous binary amine blend of Hexamethylenediamine (HMDA) and 2-Dimethylaminoethanol (DMAE)," Energy, Elsevier, vol. 296(C).
    7. Palhazi Cuervo, Daniel & Goos, Peter & Sörensen, Kenneth, 2017. "An algorithmic framework for generating optimal two-stratum experimental designs," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 224-249.
    8. Chen, Baixi & Li, Zhiming & Li, Zhi & Peng, Can, 2023. "The calculation of alias pattern in three-level regular designs," Statistics & Probability Letters, Elsevier, vol. 202(C).
    9. Goos, Peter & Vandebroek, Martina, 2001. "-optimal response surface designs in the presence of random block effects," Computational Statistics & Data Analysis, Elsevier, vol. 37(4), pages 433-453, October.
    10. Mohammed A. Alomair & Stelios D. Georgiou & Manohar Aggarwal, 2020. "Projection properties of three‐level screening designs," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 62(4), pages 407-425, December.
    11. Emanuele Borgonovo & Elmar Plischke & Giovanni Rabitti, 2022. "Interactions and computer experiments," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1274-1303, September.
    12. Butler, Neil A., 2004. "Minimum G2-aberration properties of two-level foldover designs," Statistics & Probability Letters, Elsevier, vol. 67(2), pages 121-132, April.
    13. Smucker, Byran J. & Jensen, Willis & Wu, Zichen & Wang, Bo, 2017. "Robustness of classical and optimal designs to missing observations," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 251-260.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecosta:v:28:y:2023:i:c:p:138-154. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/econometrics-and-statistics .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.