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Samurai Sudoku-Based Space-Filling Designs for Data Pooling

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  • Xu Xu
  • Peter Z. G. Qian
  • Qing Liu

Abstract

Pooling data from multiple sources plays an increasingly vital role in today’s world. By using a popular Sudoku game, we propose a new type of design, called a Samurai Sudoku-based space-filling design to address this issue. Such a design is an orthogonal array-based Latin hypercube design with the following attractive properties: (i) the complete design achieves uniformity in both univariate and bivariate margins; (ii) it can be divided into groups of subdesigns with overlaps such that each subdesign achieves uniformity in both univariate and bivariate margins; and (iii) each of the overlaps achieves uniformity in both univariate and bivariate margins. Examples are given to illustrate the properties of the proposed design, and to demonstrate the advantages of using the proposed design for pooling data from multiple sources.[Received August 2013. Revised July 2015.]

Suggested Citation

  • Xu Xu & Peter Z. G. Qian & Qing Liu, 2016. "Samurai Sudoku-Based Space-Filling Designs for Data Pooling," The American Statistician, Taylor & Francis Journals, vol. 70(1), pages 1-8, February.
    • Handle: RePEc:taf:amstat:v:70:y:2016:i:1:p:1-8
    DOI: 10.1080/00031305.2015.1114970
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    References listed on IDEAS

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    1. Xu Xu & BEN Haaland & Peter Z. G. Qian, 2011. "Sudoku-based space-filling designs," Biometrika, Biometrika Trust, vol. 98(3), pages 711-720.
    2. Nicholas Horton & Garrett Fitzmaurice, 2005. "Analysis of multiple source/multiple informant data in Stata," North American Stata Users' Group Meetings 2005 1, Stata Users Group.
    3. Lohr, Sharon & Rao, J.N.K., 2006. "Estimation in Multiple-Frame Surveys," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1019-1030, September.
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