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Categorical Functional Data Analysis. The cfda R Package

Author

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  • Cristian Preda

    (UMR CNRS 8524—Laboratoire Paul Painlevé, University of Lille, 59000 Lille, France
    Institute of Statistics and Applied Mathematics of the Romanian Academy, 050711 Bucharest, Romania
    Inria Lille Nord-Europe, MODAL, 59655 Villeneuve d’Ascq, France)

  • Quentin Grimonprez

    (DiagRAMS Technologies, 59000 Lille, France)

  • Vincent Vandewalle

    (Inria Lille Nord-Europe, MODAL, 59655 Villeneuve d’Ascq, France
    Biostatistics Department, University of Lille, CHU Lille—ULR 2694 METRICS, 59000 Lille, France)

Abstract

Categorical functional data represented by paths of a stochastic jump process with continuous time and a finite set of states are considered. As an extension of the multiple correspondence analysis to an infinite set of variables, optimal encodings of states over time are approximated using an arbitrary finite basis of functions. This allows dimension reduction, optimal representation, and visualisation of data in lower dimensional spaces. The methodology is implemented in the cfda R package and is illustrated using a real data set in the clustering framework.

Suggested Citation

  • Cristian Preda & Quentin Grimonprez & Vincent Vandewalle, 2021. "Categorical Functional Data Analysis. The cfda R Package," Mathematics, MDPI, vol. 9(23), pages 1-31, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:23:p:3074-:d:691113
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    References listed on IDEAS

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