autoMFA-package: autoMFA: Algorithms for Automatically Fitting MFA Models

In autoMFA: Algorithms for Automatically Fitting MFA Models

Description

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.

Author(s)

Maintainer: John Davey [e-mail]

Other contributors:

• Sharon Lee [contributor]

• Garique Glonek [contributor]

• Suren Rathnayake [contributor]

• Geoff McLachlan [contributor]

• Albert Ali Salah [contributor]

• Heysem Kaya [contributor]

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