IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v77y2007i15p1567-1573.html
   My bibliography  Save this article

Construction of fractional factorial split-plot designs with weak minimum aberration

Author

Listed:
  • Yang, Jianfeng
  • Zhang, Runchu
  • Liu, Minqian

Abstract

Fractional factorial split-plot (FFSP) designs with minimum aberration have been applied in industrial experiments. But, they are not so easy to construct for cases having many whole plot (or subplot) factors and only few subplot (or whole plot) factors. Weak minimum aberration is a weak version of minimum aberration. Based on the theory of complementary designs, this paper provides some theoretical results which are useful for constructing FFSP designs with weak minimum aberration. From these results, many such FFSP designs are constructed and tabulated, and it is further shown that quite a few of them are also minimum aberration designs.

Suggested Citation

  • Yang, Jianfeng & Zhang, Runchu & Liu, Minqian, 2007. "Construction of fractional factorial split-plot designs with weak minimum aberration," Statistics & Probability Letters, Elsevier, vol. 77(15), pages 1567-1573, September.
    • Handle: RePEc:eee:stapro:v:77:y:2007:i:15:p:1567-1573
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(07)00131-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. D. R. Bingham & E. D. Schoen & R. R. Sitter, 2005. "Corrigendum: Designing fractional factorial split‐plot experiments with few whole‐plot factors," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(5), pages 955-958, November.
    2. D. R. Bingham & E. D. Schoen & R. R. Sitter, 2004. "Designing fractional factorial split‐plot experiments with few whole‐plot factors," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(2), pages 325-339, April.
    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. 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.
    2. K. Chatterjee & C. Koukouvinos, 2021. "Construction of mixed-level supersaturated split-plot designs," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(7), pages 949-967, October.
    3. Smucker, Byran J. & Castillo, Enrique del & Rosenberger, James L., 2012. "Model-robust designs for split-plot experiments," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4111-4121.
    4. Minyang Hu & Shengli Zhao, 2022. "Minimum Aberration Split-Plot Designs Focusing on the Whole Plot Factors," Mathematics, MDPI, vol. 10(5), pages 1-12, February.
    5. Bradley Jones & Peter Goos, 2009. "D-optimal design of split-split-plot experiments," Biometrika, Biometrika Trust, vol. 96(1), pages 67-82.
    6. K. Chatterjee & C. Koukouvinos & K. Mylona, 2020. "Construction of supersaturated split-plot designs," Statistical Papers, Springer, vol. 61(5), pages 2203-2219, October.
    7. Murat Kulahci & John Tyssedal, 2017. "Split-plot designs for multistage experimentation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(3), pages 493-510, February.
    8. ARNOUTS, Heidi & GOOS, Peter, 2013. "Staggered-level designs for response surface modeling," Working Papers 2013027, University of Antwerp, Faculty of Business and Economics.
    9. ARNOUTS, Heidi & GOOS, Peter, 2008. "Staggered designs for experiments with more than one hard-to-change factor," Working Papers 2008018, University of Antwerp, Faculty of Business and Economics.
    10. Steven G. Gilmour & Peter Goos, 2009. "Analysis of data from non‐orthogonal multistratum designs in industrial experiments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(4), pages 467-484, September.
    11. SCHOEN, Eric D. & JONES, Bradley & GOOS, Peter, 2010. "Split-plot experiments with factor-dependent whole-plot sizes," Working Papers 2010001, University of Antwerp, Faculty of Business and Economics.

    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:stapro:v:77:y:2007:i:15:p:1567-1573. 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: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.