| Name : R-seedCCA
| |
| Version : 3.1
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.9.4
| Date : 2024-06-14 12:13:08
|
| Group : Development/Libraries/Other
| Source RPM : R-seedCCA-3.1-lp153.9.4.src.rpm
|
| Size : 0.34 MB
| |
| Packager : (none)
| |
| Summary : Seeded Canonical Correlation Analysis
|
Description :
Functions for dimension reduction through the seeded canonical
correlation analysis are provided. A classical canonical correlation
analysis (CCA) is one of useful statistical methods in multivariate
data analysis, but it is limited in use due to the matrix inversion for
large p small n data. To overcome this, a seeded CCA has been proposed
in Im, Gang and Yoo (2015) \\doi{10.1002/cem.2691}. The seeded CCA is a
two-step procedure. The sets of variables are initially reduced by
successively projecting cov(X,Y) or cov(Y,X) onto cov(X) and cov(Y),
respectively, without loss of information on canonical correlation
analysis, following Cook, Li and Chiaromonte (2007)
\\doi{10.1093/biomet/asm038} and Lee and Yoo (2014)
\\doi{10.1111/anzs.12057}. Then, the canonical correlation is finalized
with the initially-reduced two sets of variables.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
