IRLBA: Efficient and fast partial SVD of large matrices for R.
The implicitly restarted Lanczos bidiagonalization algorithm (IRLBA) of
Jim Baglama and Lothar Reichel is a state of the art method for computing
a few singular vectors and corresponding singular values of huge matrices.
The irlba package is the R language implementation of the method.
With it, you can compute partial SVDs and principal component analyses of
very large scale data. The package works well with sparse matrices and with
other matrix classes like those provided by the Bigmemory package.
The source code is available from: http://rforge.net/irlba/,
and of course the R package is available on CRAN.
The vignette documentation is here: irlba.pdf.
The slides used in the video below may be found here: