Integrated Functional Depth for Partially Observed Functional Data and applications to visualization, outlier detection and classification. It implements the methods proposed in: ElÃas, A., Jiménez, R., Paganoni, A. M. and Sangalli, L. M., (2023), "Integrated Depth for Partially Observed Functional Data", Journal of Computational and Graphical Statistics, <doi:10.1080/10618600.2022.2070171>. ElÃas, A., Jiménez, R., & Shang, H. L. (2023), "Depth-based reconstruction method for incomplete functional data", Computational Statistics, <doi:10.1007/s00180-022-01282-9>. ElÃas, A., Nagy, S. (2024), "Statistical properties of partially observed integrated functional depths", TEST, <doi:10.1007/s11749-024-00954-6>.
Version: 2.0.0 Depends: R (≥ 3.5.0) Imports: stats, ggplot2, tibble, magrittr, reshape2, patchwork, igraph Suggests: knitr, rmarkdown Published: 2025-06-25 DOI: 10.32614/CRAN.package.fdaPOIFD Author: Antonio ElÃas [aut, cre], Raúl Jiménez [ctb], Anna M. Paganoni [ctb], Laura M. Sangalli [ctb], Stanislav Nagy [ctb], Maximiliam Ofner [ctb] Maintainer: Antonio ElÃas <antonioefz91 at gmail.com> BugReports: https://github.com/aefdz/fdaPOIFD/issues License: GPL-3 URL: https://github.com/aefdz/fdaPOIFD NeedsCompilation: no Citation: fdaPOIFD citation info Materials: NEWS In views: FunctionalData CRAN checks: fdaPOIFD results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=fdaPOIFD to link to this page.
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