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Object-Oriented Software for Functional Data

Clara Happ-Kurz

2020Journal of Statistical Software21 citationsDOIOpen Access PDF

Abstract

This paper introduces the funData R package as an object-oriented implementation of functional data. It implements a unified framework for dense univariate and multivariate functional data on one- and higher dimensional domains as well as for irregular functional data. The aim of this package is to provide a user-friendly, self-contained core toolbox for functional data, including important functionalities for creating, accessing and modifying functional data objects, that can serve as a basis for other packages. The package further contains a full simulation toolbox, which is a useful feature when implementing and testing new methodological developments. Based on the theory of object-oriented data analysis, it is shown why it is natural to implement functional data in an object-oriented manner. The classes and methods provided by funData are illustrated in many examples using two freely available datasets. The MFPCA package, which implements multivariate functional principal component analysis, is presented as an example for an advanced methodological package that uses the funData package as a basis, including a case study with real data. Both packages are publicly available on GitHub and the Comprehensive R Archive Network.

Topics & Concepts

Computer scienceR packageToolboxUnivariateFunctional dependencyMultivariate statisticsSoftwareData miningFeature (linguistics)Functional specificationFunctional data analysisFunctional principal component analysisPrincipal (computer security)Functional requirementSoftware packagePrincipal component analysisFunctional designSoftware engineeringFunctional decompositionProgramming languageData structureComponent (thermodynamics)Data manipulation languageCore (optical fiber)Functional programmingFunctional testingTheoretical computer scienceSoftware frameworkData modelingMultidimensional dataStatistical Methods and InferenceBayesian Methods and Mixture ModelsSensory Analysis and Statistical Methods
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