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Exactly computing bivariate projection depth contours and median


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  • Liu, Xiaohui
  • Zuo, Yijun
  • Wang, Zhizhong
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    Among their competitors, projection depth and its induced estimators are very favorable because they can enjoy very high breakdown point robustness without having to pay the price of low efficiency, meanwhile providing a promising center-outward ordering of multi-dimensional data. However, their further applications have been severely hindered due to their computational challenge in practice. In this paper, we derive a simple form of the projection depth function, when (μ,σ)= (Med, MAD). This simple form enables us to extend the existing result of point-wise exact computation of projection depth (PD) of Zuo and Lai (2011) to depth contours and median for bivariate data.

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    Bibliographic Info

    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 60 (2013)
    Issue (Month): C ()
    Pages: 1-11

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    Handle: RePEc:eee:csdana:v:60:y:2013:i:c:p:1-11

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    Related research

    Keywords: Projection depth; Projection median; Projection depth contour; Exact computation algorithm; Linear fractional functionals programming;


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    Cited by:
    1. Zuo, Yijun, 2013. "Multidimensional medians and uniqueness," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 82-88.


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