Package: onlinePCA 1.3.2

David Degras

onlinePCA: Online Principal Component Analysis

Online PCA for multivariate and functional data using perturbation methods, low-rank incremental methods, and stochastic optimization methods.

Authors:David Degras [aut, cre], Herve Cardot [ctb]

onlinePCA_1.3.2.tar.gz
onlinePCA_1.3.2.zip(r-4.7-x86_64)onlinePCA_1.3.2.zip(r-4.7-arm64)onlinePCA_1.3.2.zip(r-4.6-x86_64)onlinePCA_1.3.2.zip(r-4.6-arm64)
onlinePCA_1.3.2.tar.gz(r-4.7-arm64)onlinePCA_1.3.2.tar.gz(r-4.7-x86_64)onlinePCA_1.3.2.tar.gz(r-4.6-arm64)onlinePCA_1.3.2.tar.gz(r-4.6-x86_64)
onlinePCA_1.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
onlinePCA/json (API)

# Install 'onlinePCA' in R:
install.packages('onlinePCA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

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

openblascpp

1.75 score 2 stars 28 scripts 248 downloads 17 exports 6 dependencies

Last updated from:4e3bc60f8b. Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK139
linux-devel-x86_64OK124
source / vignettesOK161
linux-release-arm64OK98
linux-release-x86_64OK119
windows-devel-arm64OK212
windows-devel-x86_64OK158
windows-release-arm64OK215
windows-release-x86_64OK111
wasm-releaseOK93

Exports:batchpcabsoipcaccipcacoef2fdcreate.basisfd2coefghapcaimputeincRpcaincRpca.blockincRpca.rcperturbationRpcasecularRpcasgapcasnlpcaupdateCovarianceupdateMean

Dependencies:latticeMatrixRcppRcppArmadilloRcppEigenRSpectra