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Half-region depth for stochastic processes

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  • Kuelbs, James
  • Zinn, Joel

Abstract

We study the concept of half-region depth, introduced in López-Pintado and Romo (2011). We show that for a wide variety of standard stochastic processes, such as Brownian motion and other symmetric stable processes with stationary independent increments tied down at 0, half-region depth assigns depth zero to all sample functions. To alleviate this difficulty we introduce a method of smoothing, which often not only eliminates the problem of zero depth, but allows us to extend the theoretical results on consistency in that paper up to the n level for many smoothed processes.

Suggested Citation

  • Kuelbs, James & Zinn, Joel, 2015. "Half-region depth for stochastic processes," Journal of Multivariate Analysis, Elsevier, vol. 142(C), pages 86-105.
    • Handle: RePEc:eee:jmvana:v:142:y:2015:i:c:p:86-105
    DOI: 10.1016/j.jmva.2015.07.012
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    References listed on IDEAS

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    1. Cuesta-Albertos, J.A. & Nieto-Reyes, A., 2008. "The random Tukey depth," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 4979-4988, July.
    2. López-Pintado, Sara & Romo, Juan, 2011. "A half-region depth for functional data," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1679-1695, April.
    3. Anirvan Chakraborty & Probal Chaudhuri, 2014. "On data depth in infinite dimensional spaces," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(2), pages 303-324, April.
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