Package: KFPCA 2.0

Rou Zhong

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) <arxiv:2102.01286>. Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang. (2021) <doi:10.1016/j.jmva.2021.104864>.

Authors:Rou Zhong [aut, cre], Jingxiao Zhang [aut]

KFPCA_2.0.tar.gz
KFPCA_2.0.zip(r-4.7-any)KFPCA_2.0.zip(r-4.6-any)
KFPCA_2.0.tar.gz(r-4.7-any)KFPCA_2.0.tar.gz(r-4.6-any)
KFPCA_2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
KFPCA/json (API)

# Install 'KFPCA' in R:
install.packages('KFPCA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • CD4 - CD4 cell counts

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 251 downloads 9 exports 83 dependencies

Last updated from:664025632f. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK123
source / vignettesOK205
linux-releaseOK138
windows-develOK77
windows-releaseOK77
wasm-releaseOK132

Exports:FPCscoreLSEGenDataKLGetGCVbw1DGetGCVbw2DkernfunKFPCAKFPCA_regMeanEstSparsePlot

Dependencies:ashbackportsbase64encbitopsbslibcachemcheckmatecliclustercolorspacecpp11data.tabledeSolvedigestevaluatefarverfastmapfdafdapacefdsFNNfontawesomeforeignFormulafsggplot2gluegridExtragtablehdrcdehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonlitekaderkernlabKernSmoothknitrkslabelinglatticelifecyclelocfitmagrittrMASSMatrixmclustmemoisemgcvmimemulticoolmvtnormnlmennetnumDerivpcaPPpracmaR6rainbowrappdirsRColorBrewerRcppRcppEigenRCurlrlangrmarkdownrpartrstudioapiS7sassscalesstringistringrtinytexvctrsviridisLitewithrxfunyaml