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 gmail.com> |
| License: |
GPL (≥ 3) |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
autoMFA results |
Documentation:
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