| Name : R-EMMIXmfa
| |
| Version : 2.0.14
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.1.4
| Date : 2024-06-14 11:00:10
|
| Group : Development/Libraries/Other
| Source RPM : R-EMMIXmfa-2.0.14-lp153.1.4.src.rpm
|
| Size : 0.22 MB
| |
| Packager : (none)
| |
| Summary : Mixture Models with Component-Wise Factor Analyzers
|
Description :
We provide functions to fit finite mixtures of multivariate normal or
t-distributions to data with various factor analytic structures adopted
for the covariance/scale matrices. The factor analytic structures
available include mixtures of factor analyzers and mixtures of common
factor analyzers. The latter approach is so termed because the matrix
of factor loadings is common to components before the
component-specific rotation of the component factors to make them white
noise. Note that the component-factor loadings are not common after
this rotation. Maximum likelihood estimators of model parameters are
obtained via the Expectation-Maximization algorithm. See descriptions
of the algorithms used in McLachlan GJ, Peel D (2000)
< doi:10.1002/0471721182.ch8> McLachlan GJ, Peel D (2000)
< ISBN:1-55860-707-2> McLachlan GJ, Peel D, Bean RW (2003)
< doi:10.1016/S0167-9473(02)00183-4> McLachlan GJ, Bean RW, Ben-Tovim
Jones L (2007) < doi:10.1016/j.csda.2006.09.015> Baek J, McLachlan GJ,
Flack LK (2010) < doi:10.1109/TPAMI.2009.149> Baek J, McLachlan GJ
(2011) < doi:10.1093/bioinformatics/btr112> McLachlan GJ, Baek J,
Rathnayake SI (2011) < doi:10.1002/9781119995678.ch9>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
