Package: bigPCAcpp 0.9.2

bigPCAcpp: Principal Component Analysis for 'bigmemory' Matrices

High performance principal component analysis routines that operate directly on bigmemory::big.matrix() objects. The package avoids materialising large matrices in memory by streaming data through 'BLAS' and 'LAPACK' kernels and provides helpers to derive scores, loadings, correlations, and contribution diagnostics, including utilities that stream results into 'bigmemory'-backed matrices for file-based workflows. Additional interfaces expose 'scalable' singular value decomposition, robust PCA, and robust SVD algorithms so that users can explore large matrices while tempering the influence of outliers. 'Scalable' principal component analysis is also implemented, Elgamal, Yabandeh, Aboulnaga, Mustafa, and Hefeeda (2015) <doi:10.1145/2723372.2751520>.

Authors:Frederic Bertrand [aut, cre]

bigPCAcpp_0.9.2.tar.gz
bigPCAcpp_0.9.2.zip(r-4.7)bigPCAcpp_0.9.2.zip(r-4.6)bigPCAcpp_0.9.2.zip(r-4.5)
bigPCAcpp_0.9.2.tgz(r-4.6-x86_64)bigPCAcpp_0.9.2.tgz(r-4.6-arm64)bigPCAcpp_0.9.2.tgz(r-4.5-x86_64)bigPCAcpp_0.9.2.tgz(r-4.5-arm64)
bigPCAcpp_0.9.2.tar.gz(r-4.7-arm64)bigPCAcpp_0.9.2.tar.gz(r-4.7-x86_64)bigPCAcpp_0.9.2.tar.gz(r-4.6-arm64)bigPCAcpp_0.9.2.tar.gz(r-4.6-x86_64)
bigPCAcpp_0.9.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bigPCAcpp/json (API)

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

Bug tracker:https://github.com/fbertran/bigpcacpp/issues

Pkgdown/docs site:https://fbertran.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

openblascpp

6.07 score 9 stars 1 packages 11 scripts 475 downloads 31 exports 6 dependencies

Last updated from:2ebf2a3de6. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK167
linux-devel-x86_64OK155
source / vignettesOK183
linux-release-arm64OK164
linux-release-x86_64OK161
macos-release-arm64OK122
macos-release-x86_64OK191
macos-oldrel-arm64OK110
macos-oldrel-x86_64OK253
windows-develOK136
windows-releaseOK134
windows-oldrelOK142
wasm-releaseOK159

Exports:is_filematrix_objectmake_filematrix_row_providerpca_bigmatrixpca_individual_contributionspca_individual_cos2pca_plot_biplotpca_plot_contributionspca_plot_correlation_circlepca_plot_scorespca_plot_screepca_robustpca_scores_bigmatrixpca_scores_stream_bigmatrixpca_scores_stream_filematrixpca_spcapca_spca_Rpca_spca_stream_bigmatrixpca_spca_stream_filematrixpca_stream_bigmatrixpca_stream_filematrixpca_supplementary_individualspca_supplementary_variablespca_variable_contributionspca_variable_contributions_stream_bigmatrixpca_variable_correlationspca_variable_correlations_stream_bigmatrixpca_variable_cos2pca_variable_loadingspca_variable_loadings_stream_bigmatrixsvd_bigmatrixsvd_robust

Dependencies:BHbigmemorybigmemory.sriRcppuuidwithr

Benchmarking bigPCAcpp Workflows
Overview | How the benchmarks were produced | Focused comparison with irlba | Summary statistics | Visual comparison | Session information
Rendered frombigPCA-benchmarks.Rmdusingknitr::rmarkdown

Last update: 2026-03-24
Started: 2025-10-02

Fast Principal Component Analysis for Big Data with bigPCAcpp
Introduction | Preparing a big.matrix | Running PCA with bigPCAcpp | Comparing against prcomp | Variable relationships | Visualising PCA results | Singular value decomposition helpers | Robust PCA and SVD | Next steps for larger data
Rendered frombigPCAcpp.Rmdusingknitr::rmarkdown

Last update: 2025-10-02
Started: 2025-10-01

Readme and manuals

Help Manual

Help pageTopics
bigPCAcpp: Principal Component Analysis for bigmemory MatricesbigPCAcpp-package bigPCAcpp
Benchmark timings for bigPCAcpp methodsbenchmark_results
BigPCA result objectsbigpca
Filematrix Row-Block Providerfilematrix_provider is_filematrix_object make_filematrix_row_provider
Experimental filematrix PCA helpersfilematrix_streaming_pca pca_scores_stream_filematrix pca_spca_stream_filematrix pca_stream_filematrix
Principal component analysis for 'bigmemory::big.matrix' inputspca_bigmatrix pca_individual_contributions pca_individual_cos2 pca_scores_bigmatrix pca_variable_contributions pca_variable_correlations pca_variable_cos2 pca_variable_loadings plot.bigpca print.summary.bigpca resolve_big_pointer summary.bigpca
PCA biplot helperpca_plot_biplot
Plot variable contributionspca_plot_contributions
Plot a PCA correlation circlepca_plot_correlation_circle
Plot sampled PCA scorespca_plot_scores
Scree plot for principal component importancepca_plot_scree
Plot PCA diagnostics for big data workflowspca_plots
Robust principal component analysispca_robust
Scalable principal component analysis via streaming power iterationspca_spca pca_spca_R
Streaming big.matrix PCA helperspca_scores_stream_bigmatrix pca_spca_stream_bigmatrix pca_stream_bigmatrix pca_variable_contributions_stream_bigmatrix pca_variable_correlations_stream_bigmatrix pca_variable_loadings_stream_bigmatrix
Supplementary individual diagnosticspca_supplementary_individuals
Supplementary variable diagnosticspca_supplementary_variables
Singular value decomposition for 'bigmemory::big.matrix' inputssvd_bigmatrix
Robust singular value decomposition (C++ backend)svd_robust
Iteratively reweighted singular value decompositionsvd_robust_R