tf: S3 Classes and Methods for Tidy Functional Data

Defines S3 vector data types for vectors of functional data (grid-based, spline-based or functional principal components-based) with all arithmetic and summary methods, derivation, integration and smoothing, plotting, data import and export, and data wrangling, such as re-evaluating, subsetting, sub-assigning, zooming into sub-domains, or extracting functional features like minima/maxima and their locations. The implementation allows including such vectors in data frames for joint analysis of functional and scalar variables.

Version: 0.3.4
Depends: R (≥ 4.1)
Imports: checkmate, methods, mgcv, mvtnorm, pracma, purrr, rlang, stats, vctrs (≥ 0.2.4), zoo
Suggests: covr, dplyr, knitr, refund, testthat (≥ 3.0.0)
Published: 2024-05-22
DOI: 10.32614/
Author: Fabian Scheipl ORCID iD [aut, cre], Jeff Goldsmith [aut], Julia Wrobel ORCID iD [ctb], Maximilian Muecke ORCID iD [ctb], Sebastian Fischer ORCID iD [ctb], Trevor Hastie [ctb] (softImpute author), Rahul Mazumder [ctb] (softImpute author), Chen Meng [ctb] (mogsa author)
Maintainer: Fabian Scheipl <fabian.scheipl at>
License: AGPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
In views: FunctionalData
CRAN checks: tf results


Reference manual: tf.pdf


Package source: tf_0.3.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): tf_0.3.4.tgz, r-oldrel (arm64): tf_0.3.4.tgz, r-release (x86_64): tf_0.3.4.tgz, r-oldrel (x86_64): tf_0.3.4.tgz
Old sources: tf archive

Reverse dependencies:

Reverse imports: ehymet, mlr3fda


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