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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 gmail.com> |
| 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: autoMFA_1.0.0.zip, r-release: autoMFA_1.0.0.zip, r-oldrel: autoMFA_1.0.0.zip |
| 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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.