Hola! 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. Kjetil On Fri, Mar 9, 2012 at 9:09 AM, Holger Diedrich <diedr...@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 > > ______________________________________________ > R-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
