autoMFA: Algorithms for Automatically Fitting MFA Models

Provides methods for fitting the Mixture of Factor Analyzers (MFA) model automatically. The MFA model is a mixture model where each sub-population is assumed to follow the Factor Analysis model. The Factor Analysis (FA) model is a latent variable model which assumes that observations are normally distributed, but imposes constraints on their covariance matrix. The MFA model contains two hyperparameters; g (the number of components in the mixture) and q (the number of factors in each component Factor Analysis model). Usually, the Expectation-Maximisation algorithm would be used to fit the MFA model, but this requires g and q to be known. This package treats g and q as unknowns and provides several methods which infer these values with as little input from the user as possible.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: abind, MASS, Matrix, Rfast, expm, stats, utils, Rdpack, pracma, usethis
Published: 2021-08-10
DOI: 10.32614/CRAN.package.autoMFA
Author: John Davey [aut, cre], Sharon Lee [ctb], Garique Glonek [ctb], Suren Rathnayake [ctb], Geoff McLachlan [ctb], Albert Ali Salah [ctb], Heysem Kaya [ctb]
Maintainer: John Davey <john.c.m.davey at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: autoMFA results


Reference manual: autoMFA.pdf


Package source: autoMFA_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): autoMFA_1.0.0.tgz, r-oldrel (arm64): autoMFA_1.0.0.tgz, r-release (x86_64): autoMFA_1.0.0.tgz, r-oldrel (x86_64): autoMFA_1.0.0.tgz


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