Package: pPCA 1.1

pPCA: Partial Principal Component Analysis of Partitioned Large Sparse Matrices

Performs partial principal component analysis of a large sparse matrix. The matrix may be stored as a list of matrices to be concatenated (implicitly) horizontally. Useful application includes cases where the number of total nonzero entries exceed the capacity of 32 bit integers (e.g., with large Single Nucleotide Polymorphism data).

Authors:Srika Raja [aut, cre], Somak Dutta [aut]

pPCA_1.1.tar.gz
pPCA_1.1.zip(r-4.7-x86_64)pPCA_1.1.zip(r-4.7-arm64)pPCA_1.1.zip(r-4.6-x86_64)pPCA_1.1.zip(r-4.6-arm64)pPCA_1.1.zip(r-4.5-x86_64)
pPCA_1.1.tgz(r-4.6-x86_64)pPCA_1.1.tgz(r-4.6-arm64)pPCA_1.1.tgz(r-4.5-x86_64)pPCA_1.1.tgz(r-4.5-arm64)
pPCA_1.1.tar.gz(r-4.7-arm64)pPCA_1.1.tar.gz(r-4.7-x86_64)pPCA_1.1.tar.gz(r-4.6-arm64)pPCA_1.1.tar.gz(r-4.6-x86_64)
pPCA_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
pPCA/json (API)

# Install 'pPCA' in R:
install.packages('pPCA', repos = c('https://srika1919.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/srika1919/ppca/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cpp

2.00 score 220 downloads 1 exports 5 dependencies

Last updated from:d10b4d5570. Checks:13 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE92
linux-devel-x86_64NOTE117
source / vignettesOK161
linux-release-arm64NOTE88
linux-release-x86_64NOTE113
macos-release-arm64NOTE191
macos-release-x86_64NOTE326
macos-oldrel-arm64NOTE178
macos-oldrel-x86_64NOTE346
windows-devel-arm64NOTE347
windows-devel-x86_64NOTE131
windows-release-arm64NOTE448
windows-release-x86_64NOTE106
windows-oldrel-x86_64NOTE103
wasm-releaseOK81

Exports:pPCA

Dependencies:latticeMatrixRcppRcppEigenRSpectra