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).

Version:	1.0
Depends:	R (≥ 3.0.2), methods, RSpectra (≥ 0.16-1)
Imports:	Matrix (≥ 1.1-0), Rcpp (≥ 0.11.5)
LinkingTo:	Rcpp
Suggests:	ggbiplot
Published:	2024-10-11
DOI:	10.32614/CRAN.package.pPCA
Author:	Srika Raja [aut, cre], Somak Dutta [aut]
Maintainer:	Srika Raja <sri1919 at iastate.edu>
License:	GPL-3
NeedsCompilation:	yes
CRAN checks:	pPCA results

Documentation:

Reference manual:

pPCA.pdf

Downloads:

Package source:	pPCA_1.0.tar.gz
Windows binaries:	r-devel: pPCA_1.0.zip, r-release: pPCA_1.0.zip, r-oldrel: pPCA_1.0.zip
macOS binaries:	r-release (arm64): pPCA_1.0.tgz, r-oldrel (arm64): pPCA_1.0.tgz, r-release (x86_64): pPCA_1.0.tgz, r-oldrel (x86_64): pPCA_1.0.tgz

Linking:

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