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Comments on: Exploratory functional data analysis

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  • Sara Lopez-Pintado

    (Northeastern University)

Abstract

In this invited paper we highlight some of the exploratory functional data methods described in the systematic review paper by Qu et al. (TEST, 2024. 10.1007/s11749-024-00952-8). We discuss recent developments related to functional boxplots and consider possible extensions of exploratory methods to non-Euclidean object data.

Suggested Citation

  • Sara Lopez-Pintado, 2025. "Comments on: Exploratory functional data analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 34(2), pages 494-497, June.
    • Handle: RePEc:spr:testjl:v:34:y:2025:i:2:d:10.1007_s11749-025-00968-8
    DOI: 10.1007/s11749-025-00968-8
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    References listed on IDEAS

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    1. Nagy, Stanislav & Ferraty, Frédéric, 2019. "Data depth for measurable noisy random functions," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 95-114.
    2. López-Pintado, Sara & Romo, Juan, 2009. "On the Concept of Depth for Functional Data," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 718-734.
    3. Weiyi Xie & Sebastian Kurtek & Karthik Bharath & Ying Sun, 2017. "A Geometric Approach to Visualization of Variability in Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 979-993, July.
    4. Naveen N. Narisetty & Vijayan N. Nair, 2016. "Extremal Depth for Functional Data and Applications," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1705-1714, October.
    5. Carlo Sguera & Sara López-Pintado, 2021. "A notion of depth for sparse functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 630-649, September.
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