| Name : R-REMLA
| |
| Version : 1.1
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp154.3.1
| Date : 2024-06-20 14:32:03
|
| Group : Development/Libraries/Other
| Source RPM : R-REMLA-1.1-lp154.3.1.src.rpm
|
| Size : 0.14 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Robust Expectation-Maximization Estimation for Latent Variable Models
|
Description :
Traditional latent variable models assume that the population is
homogeneous, meaning that all individuals in the population are assumed
to have the same latent structure. However, this assumption is often
violated in practice given that individuals may differ in their age,
gender, socioeconomic status, and other factors that can affect their
latent structure. The robust expectation maximization (REM) algorithm
is a statistical method for estimating the parameters of a latent
variable model in the presence of population heterogeneity as
recommended by Nieser & Cochran (2023) < doi:10.1037/met0000413>. The
REM algorithm is based on the expectation-maximization (EM) algorithm,
but it allows for the case when all the data are generated by the
assumed data generating model.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.4/x86_64 |
