[Rd] Eigenvalue calculation of sparse matrices

Kjetil Halvorsen kjetilbrinchmannhalvorsen at gmail.com
Sun Mar 11 00:02:29 CET 2012


This can be done with the CRAN package igraph, which contains (part
of) the arpack
library for computing only some eigenvalues/eigenvectors of sparse
matrices. arpack gives you the option of computing a few of the
smallest or a few of the largest eigenvalues/vectors.

You will need yourself to wrte a function doing matrix-vector
multiplication, so the arpack
methods itself is independent of the implementation of your sparse matrix.


On Fri, Mar 9, 2012 at 9:09 AM, Holger Diedrich
<diedrich at math.uni-potsdam.de> wrote:
> Dear all,
> I am currently working on the calculation of eigenvalues (and -vectors) of
> large matrices. Since these are mostly sparse matrices and I remember some
> specific functionalities in MATLAB for sparse matrices, I started a research
> how to optimize the calculation of eigenvalues of a sparse matrix.
> The function eigen itself works with the LAPACK library which has no special
> handling for sparse matrices, same for the EISPACK library. The ARPACK
> library is capable to work with sparse matrices but I couldn't find any
> useful R package using ARPACK.
> The Matrix package can handle sparse matrices but has no further useful
> functionalities (concerning my tasks).
> Does one of you have any advice how to optimize the eigenvalue calculation
> of sparse matrices in R?
> Thanks in advance,
> Holger
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