You can use the power method for computing the dominant eigenvector. A more sophisticated approach (for large matrices) is the Lancsoz algorithm for Hermitian matrices, which is based on the power method. The `arpack' function in the "igraph" package uses the more general Arnoldi iteration, which is the generailzation of Lancsoz algorithm for non-Hermitian matrices.
Ravi. ____________________________________________________________________ Ravi Varadhan, Ph.D. Assistant Professor, Division of Geriatric Medicine and Gerontology School of Medicine Johns Hopkins University Ph. (410) 502-2619 email: rvarad...@jhmi.edu ----- Original Message ----- From: MInh Tang <mht...@cs.indiana.edu> Date: Saturday, June 12, 2010 12:37 pm Subject: [R] Fast way to compute largest eigenvector To: r-h...@stat.math.ethz.ch > Hello all, > > I was wondering if there is a function in R that only computes the > eigenvector > corresponding to the largest/smallest eigenvalue of an arbitrary real > matrix. > > Thanks > Minh > > -- > Living on Earth may be expensive, but it includes an annual free trip > around the Sun. > > ______________________________________________ > R-help@r-project.org mailing list > > PLEASE do read the posting guide > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
