| Name : R-sparseEigen
| |
| Version : 0.1.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.2.13
| Date : 2024-06-14 11:13:56
|
| Group : Development/Libraries/Other
| Source RPM : R-sparseEigen-0.1.0-lp153.2.13.src.rpm
|
| Size : 0.39 MB
| |
| Packager : (none)
| |
| Summary : Computation of Sparse Eigenvectors of a Matrix
|
Description :
Computation of sparse eigenvectors of a matrix (aka sparse PCA) with
running time 2-3 orders of magnitude lower than existing methods and
better final performance in terms of recovery of sparsity pattern and
estimation of numerical values. Can handle covariance matrices as well
as data matrices with real or complex-valued entries. Different levels
of sparsity can be specified for each individual ordered eigenvector
and the method is robust in parameter selection. See vignette for a
detailed documentation and comparison, with several illustrative
examples. The package is based on the paper: K. Benidis, Y. Sun, P.
Babu, and D. P. Palomar (2016). \"Orthogonal Sparse PCA and Covariance
Estimation via Procrustes Reformulation,\" IEEE Transactions on Signal
Processing < doi:10.1109/TSP.2016.2605073>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
