  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 CRAN.

Computation