The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

KFPCA: Kendall Functional Principal Component Analysis

Implementation for Kendall functional principal component analysis. Kendall functional principal component analysis is a robust functional principal component analysis technique for non-Gaussian functional/longitudinal data. The crucial function of this package is KFPCA() and KFPCA_reg(). Moreover, least square estimates of functional principal component scores are also provided. Refer to Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang. (2021) <doi:10.48550/arXiv.2102.01286>. Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang. (2021) <doi:10.1016/j.jmva.2021.104864>.

Version: 2.0
Depends: R (≥ 2.10)
Imports: kader, utils, pracma, fdapace, fda, stats, graphics
Published: 2022-02-04
DOI: 10.32614/CRAN.package.KFPCA
Author: Rou Zhong [aut, cre], Jingxiao Zhang [aut]
Maintainer: Rou Zhong <zhong_rou at 163.com>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: KFPCA results

Documentation:

Reference manual: KFPCA.pdf

Downloads:

Package source: KFPCA_2.0.tar.gz
Windows binaries: r-devel: KFPCA_2.0.zip, r-release: KFPCA_2.0.zip, r-oldrel: KFPCA_2.0.zip
macOS binaries: r-release (arm64): KFPCA_2.0.tgz, r-oldrel (arm64): KFPCA_2.0.tgz, r-release (x86_64): KFPCA_2.0.tgz, r-oldrel (x86_64): KFPCA_2.0.tgz
Old sources: KFPCA archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=KFPCA to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.