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A central limit theorem for marginally coupled designs

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  • Wang, Sumin
  • Wang, Dongying
  • Sun, Fasheng

Abstract

In this paper, we derive a central limit theorem for marginally coupled designs that are intended for computer experiments with both qualitative and quantitative factors. This result is useful for establishing confidence intervals for estimators in various statistical applications.

Suggested Citation

  • Wang, Sumin & Wang, Dongying & Sun, Fasheng, 2019. "A central limit theorem for marginally coupled designs," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 168-174.
    • Handle: RePEc:eee:stapro:v:146:y:2019:i:c:p:168-174
    DOI: 10.1016/j.spl.2018.11.018
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    References listed on IDEAS

    as
    1. Cox, Dennis D. & Park, Jeong-Soo & Singer, Clifford E., 2001. "A statistical method for tuning a computer code to a data base," Computational Statistics & Data Analysis, Elsevier, vol. 37(1), pages 77-92, July.
    2. Peter Z. G. Qian, 2012. "Sliced Latin Hypercube Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 393-399, March.
    3. Fasheng Sun & Min-Qian Liu & Dennis K. J. Lin, 2009. "Construction of orthogonal Latin hypercube designs," Biometrika, Biometrika Trust, vol. 96(4), pages 971-974.
    4. Fasheng Sun & Boxin Tang, 2017. "A Method of Constructing Space-Filling Orthogonal Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 683-689, April.
    5. C. Devon Lin & Rahul Mukerjee & Boxin Tang, 2009. "Construction of orthogonal and nearly orthogonal Latin hypercubes," Biometrika, Biometrika Trust, vol. 96(1), pages 243-247.
    6. Yong-Dao Zhou & Hongquan Xu, 2014. "Space-Filling Fractional Factorial Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1134-1144, September.
    Full references (including those not matched with items on IDEAS)

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