Categorical Functional Data Analysis. The cfda R Package

Cristian Preda, Quentin Grimonprez and Vincent Vandewalle
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Cristian Preda: UMR CNRS 8524—Laboratoire Paul Painlevé, University of Lille, 59000 Lille, France
Quentin Grimonprez: DiagRAMS Technologies, 59000 Lille, France
Vincent Vandewalle: Inria Lille Nord-Europe, MODAL, 59655 Villeneuve d’Ascq, France

Mathematics, 2021, vol. 9, issue 23, 1-31

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.

Keywords: functional data; categorical data; stochastic process; multiple correspondence analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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