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Robust functional principal components for irregularly spaced longitudinal data

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  • Ricardo A. Maronna

    (University of La Plata)

Abstract

Consider longitudinal data $$x_{ij},$$ x ij , with $$i=1,...,n$$ i = 1 , . . . , n and $$j=1,...,p,$$ j = 1 , . . . , p , where $$x_{ij}$$ x ij is the observation of the smooth random function $$X_{i}\left( .\right) $$ X i . at time $$t_{j}.$$ t j . The goal of this paper is to develop a parsimonious representation of the data by a linear combination of a set of $$q

Suggested Citation

  • Ricardo A. Maronna, 2021. "Robust functional principal components for irregularly spaced longitudinal data," Statistical Papers, Springer, vol. 62(4), pages 1563-1582, August.
    • Handle: RePEc:spr:stpapr:v:62:y:2021:i:4:d:10.1007_s00362-019-01147-2
    DOI: 10.1007/s00362-019-01147-2
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    References listed on IDEAS

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    1. N. Locantore & J. Marron & D. Simpson & N. Tripoli & J. Zhang & K. Cohen & Graciela Boente & Ricardo Fraiman & Babette Brumback & Christophe Croux & Jianqing Fan & Alois Kneip & John Marden & Daniel P, 1999. "Robust principal component analysis for functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 8(1), pages 1-73, June.
    2. Lee, Seokho & Shin, Hyejin & Billor, Nedret, 2013. "M-type smoothing spline estimators for principal functions," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 89-100.
    3. Graciela Boente & Matías Salibian-Barrera, 2015. "S -Estimators for Functional Principal Component Analysis," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1100-1111, September.
    4. Tomasz Górecki & Mirosław Krzyśko & Łukasz Waszak & Waldemar Wołyński, 2018. "Selected statistical methods of data analysis for multivariate functional data," Statistical Papers, Springer, vol. 59(1), pages 153-182, March.
    5. Yao, Fang & Muller, Hans-Georg & Wang, Jane-Ling, 2005. "Functional Data Analysis for Sparse Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 577-590, June.
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    Cited by:

    1. Park, Yeonjoo & Kim, Hyunsung & Lim, Yaeji, 2023. "Functional principal component analysis for partially observed elliptical process," Computational Statistics & Data Analysis, Elsevier, vol. 184(C).

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