irlba (2.1.2)

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Fast Truncated SVD, PCA and Symmetric Eigendecomposition for Large Dense and Sparse Matrices.

http://cran.r-project.org/web/packages/irlba

Fast and memory efficient methods for truncated singular and eigenvalue decompositions and principal component analysis of large sparse or dense matrices.

Maintainer: B. W. Lewis
Author(s): Jim Baglama [aut, cph], Lothar Reichel [aut, cph], B. W. Lewis [aut, cre, cph]

License: GPL-3

Uses: Matrix
Reverse depends: DDRTree, s4vd, semisupKernelPCA
Reverse suggests: KernelKnn, logisticPCA, steadyICA

Released 6 months ago.


6 previous versions

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