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:
onlinePCA_1.3.2.tar.gz
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✨
card.svg |card.png
onlinePCA/json (API)
NEWS
| # Install 'onlinePCA' in R: |
| install.packages('onlinePCA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:4e3bc60f8b. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 136 | ||
| linux-devel-x86_64 | OK | 139 | ||
| source / vignettes | OK | 180 | ||
| linux-release-arm64 | OK | 133 | ||
| linux-release-x86_64 | OK | 135 | ||
| wasm-release | OK | 139 |
Exports:batchpcabsoipcaccipcacoef2fdcreate.basisfd2coefghapcaimputeincRpcaincRpca.blockincRpca.rcperturbationRpcasecularRpcasgapcasnlpcaupdateCovarianceupdateMean
Dependencies:latticeMatrixRcppRcppArmadilloRcppEigenRSpectra
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Online Principal Component Analysis | onlinePCA-package |
| Batch PCA | batchpca |
| Block Stochastic Orthononal Iteration (BSOI) | bsoipca |
| Candid Covariance-Free Incremental PCA | ccipca |
| Recover functional data from their B-spline coefficients | coef2fd |
| Create a smooth B-spline basis | create.basis |
| Compute the coefficients of functional data in a B-spline basis | fd2coef |
| Generalized Hebbian Algorithm for PCA | ghapca |
| BLUP Imputation of Missing Values | impute |
| Incremental PCA | incRpca |
| Incremental PCA with Block Update | incRpca.block |
| Incremental PCA With Reduced Complexity | incRpca.rc |
| Recursive PCA using a rank 1 perturbation method | perturbationRpca |
| Recursive PCA Using Secular Equations | secularRpca |
| Stochastic Gradient Ascent PCA | sgapca |
| Subspace Network Learning PCA | snlpca |
| Update the Sample Covariance Matrix | updateCovariance |
| Update the Sample Mean Vector | updateMean |