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irlba

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

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

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

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

Principal Components Analysis

Sparse regularized low-rank matrix approximation.

Summary method for truncated pca objects computed by prcomp_irlba.

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

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

v2.3.3

GPL-3

Authors

Jim Baglama [aut, cph], Lothar Reichel [aut, cph], B. W. Lewis [aut, cre, cph]

Initial release

2019-02-04

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