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EMMIXmfa  

Mixture Models with Component-Wise Factor Analyzers
View on CRAN: Click here


Download and install EMMIXmfa package within the R console
Install from CRAN:
install.packages("EMMIXmfa")

Install from Github:
library("remotes")
install_github("cran/EMMIXmfa")

Install by package version:
library("remotes")
install_version("EMMIXmfa", "2.0.14")



Attach the package and use:
library("EMMIXmfa")
Maintained by
Suren Rathnayake
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-10-19
Latest Update: 2019-12-16
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) McLachlan GJ, Peel D (2000) McLachlan GJ, Peel D, Bean RW (2003) McLachlan GJ, Bean RW, Ben-Tovim Jones L (2007) Baek J, McLachlan GJ, Flack LK (2010) Baek J, McLachlan GJ (2011) McLachlan GJ, Baek J, Rathnayake SI (2011) .
How to cite:
Suren Rathnayake (2018). EMMIXmfa: Mixture Models with Component-Wise Factor Analyzers. R package version 2.0.14, https://cran.r-project.org/web/packages/EMMIXmfa. Accessed 03 Dec. 2024.
Previous versions and publish date:
2.0.7 (2018-10-19 14:20), 2.0.11 (2019-12-16 23:50)
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