search for: eigenproblems

...function i see to do this in R_ext/Lapack.h is dsyevx. however, i know that in LAPACK dsyevr can also return a partial eigendecomposition. why is dsyevr not exported in R_ext/Lapack.h? my superficial understanding is that dsyevr is "better" (faster? stabler?) for both complete and partial eigenproblems than dsyevd/dsyevx, but only the complete eigenproblem interface to dsyevr appears to be exported in Lapack.h (as dsyev). corrections to misunderstandings in the above are welcome. advice on whether using dsyevr rather than dsyevx is (very) important for partial decompositions is also gratefully a...

...function i see to do this in R_ext/Lapack.h is dsyevx. however, i know that in LAPACK dsyevr can also return a partial eigendecomposition. why is dsyevr not exported in R_ext/Lapack.h? my superficial understanding is that dsyevr is "better" (faster? stabler?) for both complete and partial eigenproblems than dsyevd/dsyevx, but only the complete eigenproblem interface to dsyevr appears to be exported in Lapack.h (as dsyev). corrections to misunderstandings in the above are welcome. advice on whether using dsyevr rather than dsyevx is (very) important for partial decompositions is also gratefully a...

Full_Name: Pierre Legendre Version: 2.1.1 OS: Mac OSX 10.4.3 Submission from: (NULL) (132.204.120.81) I am reporting the mis-behaviour of the function 'eigen' in 'base', for the following input matrix: A <- matrix(c(2,3,4,-1,3,1,1,-2,0),3,3) eigen(A) I obtain the following results, which are incorrect for eigenvalues and eigenvectors 2 and 3 (incorrect imaginary portions):

I need to compute generalized eigenvalues. The eigen function in base doesn't do it and I can't find a package that does. As I understand it, Lapack __can__ computer them (http://www.netlib.org/lapack/lawn41/node111.html) and R can use Lapack. If there is no function already, can I access Lapack from R and use those routines directly? Thank you, Joshua Gilbert.

This thread reveals that R has some holes in the solution of some of the linear algebra problems that may arise. It looks like Jim Ramsay used a quick and dirty approach to the generalized eigenproblem by using B^(-1) %*% A, which is usually not too successful due to issues with condition of B and making a symmetric/Hermitian problem unsymmetric. In short, the problem is stated as follows:

G'Day R users! Following an ordination using prcomp, I'd like to test which variables singnificantly contribute to a principal component. There is a method suggested by Peres-Neto and al. 2003. Ecology 84:2347-2363 called "bootstrapped eigenvector". It was asked for that in this forum in January 2005 by J?r?me Lema?tre: "1) Resample 1000 times with replacement entire