Package: funpca 9.0

funpca: Functional Principal Component Analysis

Functional principal component analysis under the Linear Mixed Models representation of smoothing splines. The method utilizes the Demmler-Reinsch basis and assumes error independence. For more details see: F. Rosales (2016) <https://ediss.uni-goettingen.de/handle/11858/00-1735-0000-0028-87F9-6>.

Authors:Francisco Rosales [aut, cph, cre], Tatyana Krivobokova [con, ths]

funpca_9.0.tar.gz
funpca_9.0.zip(r-4.7)funpca_9.0.zip(r-4.6)funpca_9.0.zip(r-4.5)
funpca_9.0.tgz(r-4.6-any)funpca_9.0.tgz(r-4.5-any)
funpca_9.0.tar.gz(r-4.7-any)funpca_9.0.tar.gz(r-4.6-any)
funpca_9.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
funpca/json (API)

# Install 'funpca' in R:
install.packages('funpca', repos = c('https://lfrm.r-universe.dev', 'https://cloud.r-project.org'))

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 256 downloads 5 exports 44 dependencies

Last updated from:92ab27c7fa. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK141
source / vignettesOK175
linux-release-x86_64OK144
macos-release-arm64OK100
macos-oldrel-arm64OK104
windows-develOK86
windows-releaseOK103
windows-oldrelOK98
wasm-releaseOK138

Exports:funpcafunpcaEstplot.funpcaprint.funpcasummary.funpca

Dependencies:ashbitopsBrobdingnagcliclustercolorspacecpp11deSolvefarverfdafdsFNNggplot2gluegtablehdrcdeisobandkernlabKernSmoothkslabelinglatticelifecyclelocfitMASSMatrixmclustmgcvmulticoolmvtnormnlmepcaPPpracmaR6rainbowRColorBrewerRcppRCurlrlangS7scalesvctrsviridisLitewithr