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irlba (version 2.3.3)

Fast Truncated Singular Value Decomposition and Principal Components Analysis for Large Dense and Sparse Matrices

Description

Fast and memory efficient methods for truncated singular value decomposition and principal components analysis of large sparse and dense matrices.

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Version

Install

install.packages('irlba')

Monthly Downloads

43,558

Version

2.3.3

License

GPL-3

Maintainer

B. Lewis

Last Published

February 5th, 2019

Functions in irlba (2.3.3)

summary.irlba_prcomp

Summary method for truncated pca objects computed by prcomp_irlba.
ssvd

Sparse regularized low-rank matrix approximation.
prcomp_irlba

Principal Components Analysis
svdr

Find a few approximate largest singular values and corresponding singular vectors of a matrix.
partial_eigen

Find a few approximate largest eigenvalues and corresponding eigenvectors of a symmetric matrix.
irlba

Find a few approximate singular values and corresponding singular vectors of a matrix.