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Big Data in context and robustness against heterogeneity


  • Marron, J.S.


The phrase Big Data has generated substantial current discussion within and outside of the field of statistics. Some personal observations about this phenomenon are discussed. One contribution is to put this set of ideas into a larger historical context. Another is to point out the related important concept of robustness against data heterogeneity, and some earlier methods which had that property, and also to discuss a number of interesting open problems motivated by this concept.

Suggested Citation

  • Marron, J.S., 2017. "Big Data in context and robustness against heterogeneity," Econometrics and Statistics, Elsevier, vol. 2(C), pages 73-80.
  • Handle: RePEc:eee:ecosta:v:2:y:2017:i:c:p:73-80
    DOI: 10.1016/j.ecosta.2016.06.001

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    References listed on IDEAS

    1. Peter Hall & J. S. Marron & Amnon Neeman, 2005. "Geometric representation of high dimension, low sample size data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(3), pages 427-444, June.
    2. Marron, J.S. & Todd, Michael J. & Ahn, Jeongyoun, 2007. "Distance-Weighted Discrimination," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1267-1271, December.
    3. John Shawe-Taylor & Keith Howker & Phil Gosset & Mark Hyland & Herman Verrelst & Yves Moreau & Christof Stoermann & Peter Burge, 2000. "Novel Techniques for Profiling and Fraud Detection in Mobile Telecommunications," World Scientific Book Chapters,in: Business Applications Of Neural Networks The State-of-the-Art of Real-World Applications, chapter 8, pages 113-139 World Scientific Publishing Co. Pte. Ltd..
    4. Makoto Aoshima & Kazuyoshi Yata, 2014. "A distance-based, misclassification rate adjusted classifier for multiclass, high-dimensional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(5), pages 983-1010, October.
    5. Xiaosun Lu & J. S. Marron & Perry Haaland, 2014. "Object-Oriented Data Analysis of Cell Images," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 548-559, June.
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    Big data; Robustness against heterogeneity;


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