irlba (2.3.3)

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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.

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: broom, ChemoSpec, ChemoSpec2D, ChemoSpecUtils, DrImpute, KernelKnn, logisticPCA, metR, Rtsne, sctransform, steadyICA, widyr

Released about 1 year ago.

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