rsvd: Randomized Singular Value Decomposition

Randomized singular value decomposition (rsvd) is a very fast probabilistic algorithm that can be used to compute the near optimal low-rank singular value decomposition of massive data sets with high accuracy. SVD plays a central role in data analysis and scientific computing. SVD is also widely used for computing (randomized) principal component analysis (PCA), a linear dimensionality reduction technique. Randomized PCA (rpca) uses the approximated singular value decomposition to compute the most significant principal components. This package also includes a function to compute (randomized) robust principal component analysis (RPCA). In addition several plot functions are provided.

Author
N. Benjamin Erichson [aut, cre]
Date of publication
2016-07-29 06:41:14
Maintainer
N. Benjamin Erichson <nbe@st-andrews.ac.uk>
License
GPL (>= 2)
Version
0.6
URLs

View on CRAN

Man pages

ggbiplot
Biplot for 'rPCA' using ggplot2
ggcorplot
Correlation plot
ggscreeplot
Pretty Screeplot
plot.rpca
Screeplot
reigen
Randomized Spectral Decomposition of a matrix (reigen).
rpca
Randomized principal component analysis (rpca).
rrpca
Randomized robust principal component analysis (rrpca).
rsvd
Randomized Singular Value Decomposition (rsvd).
tiger
Tiger

Files in this package

rsvd
rsvd/tests
rsvd/tests/testthat
rsvd/tests/testthat/test_rrpca.R
rsvd/tests/testthat/test_rsvd.R
rsvd/tests/testthat/test_rpca.R
rsvd/tests/testthat/test_dependency.R
rsvd/tests/testthat/test_reigen.R
rsvd/NAMESPACE
rsvd/data
rsvd/data/tiger.RData
rsvd/data/datalist
rsvd/R
rsvd/R/reigen.R
rsvd/R/rrpca.R
rsvd/R/ggbiplot.R
rsvd/R/tiger.R
rsvd/R/plots.R
rsvd/R/rpca.R
rsvd/R/wrapper_function.R
rsvd/R/rsvd.R
rsvd/MD5
rsvd/DESCRIPTION
rsvd/man
rsvd/man/tiger.Rd
rsvd/man/rrpca.Rd
rsvd/man/plot.rpca.Rd
rsvd/man/rpca.Rd
rsvd/man/reigen.Rd
rsvd/man/ggscreeplot.Rd
rsvd/man/ggcorplot.Rd
rsvd/man/rsvd.Rd
rsvd/man/ggbiplot.Rd