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:
KFPCA_2.0.tar.gz
KFPCA_2.0.tar.gz(r-4.5-noble)KFPCA_2.0.tar.gz(r-4.4-noble)
KFPCA_2.0.tgz(r-4.4-emscripten)KFPCA_2.0.tgz(r-4.3-emscripten)
KFPCA.pdf |KFPCA.html✨
KFPCA/json (API)
| # Install 'KFPCA' in R: |
| install.packages('KFPCA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- CD4 - CD4 cell counts
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:664025632f. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 02 2024 |
| R-4.5-linux | OK | Dec 02 2024 |
Exports:FPCscoreLSEGenDataKLGetGCVbw1DGetGCVbw2DkernfunKFPCAKFPCA_regMeanEstSparsePlot
Dependencies:ashbackportsbase64encbitopsbslibcachemcheckmatecliclustercolorspacedata.tabledeSolvedigestevaluatefansifarverfastmapfdafdapacefdsFNNfontawesomeforeignFormulafsggplot2gluegridExtragtablehdrcdehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonlitekaderkernlabKernSmoothknitrkslabelinglatticelifecyclelocfitmagrittrMASSMatrixmclustmemoisemgcvmimemulticoolmunsellmvtnormnlmennetnumDerivpcaPPpillarpkgconfigpracmaR6rainbowrappdirsRColorBrewerRcppRcppEigenRCurlrlangrmarkdownrpartrstudioapisassscalesstringistringrtibbletinytexutf8vctrsviridisviridisLitewithrxfunyaml
