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.

Package details

AuthorJohn Davey [aut, cre], Sharon Lee [ctb], Garique Glonek [ctb], Suren Rathnayake [ctb], Geoff McLachlan [ctb], Albert Ali Salah [ctb], Heysem Kaya [ctb]
MaintainerJohn Davey <john.c.m.davey@gmail.com>
LicenseGPL (>= 3)
Version1.0.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("autoMFA")

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autoMFA documentation built on Aug. 10, 2021, 5:07 p.m.