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(). Moreover, least square estimates of functional principal component scores are also provided. Refer to <arXiv:2102.00911>.

Version: 1.0
Depends: R (≥ 2.10)
Imports: kader, utils, pracma, fdapace, fda, stats, graphics
Published: 2021-02-11
Author: Rou Zhong [aut, cre]
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_1.0.tar.gz
Windows binaries: r-devel: KFPCA_1.0.zip, r-release: KFPCA_1.0.zip, r-oldrel: KFPCA_1.0.zip
macOS binaries: r-release (arm64): KFPCA_1.0.tgz, r-release (x86_64): KFPCA_1.0.tgz, r-oldrel: KFPCA_1.0.tgz

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