Fixed BLAS/LAPACK calls, thanks to Prof. Ripley.
Updated Spectra to v0.8.1.
eigs() now detects the symmetry of dgRMatrix matrices.
(Internal) Replaced the deprecated
class in the C++ code.
Updated Spectra to v0.8.0.
to allow users supplying the initial vector for the algorithm.
Updated Spectra to v0.6.2 that fixes regressions in v0.6.1 on some edge cases.
Using prettydoc to format vignette.
Updated Spectra to v0.6.1 that improves numerical accuracy of eigen-solvers.
Registered native routines per CRAN's policy.
svds() supports user-defined implicit matrix that is
specified by two functions,
calculate the matrix multiplication and transpose multiplication
Added a package vignette.
New package to supersede rARPACK to avoid name confusion.
Imported from rARPACK 0.10-0.
Improved numerical stability.
Fixed convergence failure for matrices that have repeated eigenvalues.
Updated the backend Spectra library, which fixed the compatibility with Eigen >= 3.2.6.
Fixed a bug that causes the algorithm not converging on some matrices.
Fixed a compilation problem on Solaris.
The backend program is now changed from ARPACK to Spectra, which brings cleaner code and better performance.
eigs_sym() now accepts more matrix types.
Added a C interface for other packages to link to.
Support for implicit matrix, contributed by Jiali Mei.
User can supply a function
FUN rather than an explicit
eigs(), and the eigenvalues/eigenvectors of this
operator will be computed.
FUN(x, args) must return a vector
of the same length as
eigs() will test the symmetry of matrix before actual
computation, since symmetric matrices can guarantee real
eigenvalues and eigenvectors, and the numerical result is more
C++ code of
svds() is completely rewritten. Now it is more
readable and easier to maintain.
Fix a bug possibly coming from ARPACK, which sometimes gives incorrect result of complex eigenvectors.
Avoid using a C random number generator.
Add support for new matrix types: dgeMatrix and dgRMatrix.
eigs() now allows a full Eigen Decomposition, meaning that
all the eigenvalues are calculated. In this case
simply a wrapper of
eigen(), and with a warning issued.
Rewrite C++ code using classes and templates.
Fix errors in checking the values of
svds() function to calculate truncated SVD.
Now sort eigenvalues in decreasing order.
eigs_sym() to avoid confusion.
Fix a matrix out-of-bound error.
Implement shift-and-invert mode for all supported eigen problems.
Update arpack-ng to 3.1.4.
eigs() supports real symmetric matrices.
eigs() supports sparse real nonsymmetric matrices of the
class dgCMatrix, defined in the Matrix package.
Initial version. For now
eigs() supports dense real