R package mcfa: Fits mixtures of common factor analyzers to a given data set. Functions for fitting mixtures of common factor analyzers (MCFA) models. MCFA models are mixture of factor analyzers (belong to the class of multivariate finite mixture models) with a common component matrix for the factor loadings before the transformation of the latent factors to be white noise. It is designed specifically for the task of displaying the observed data points in a lower (q-dimensional) space, where q is the number of factors adopted in the factor-analytic representation of the observed vector. The mcfa function fits mixtures common factor analyzers where the components distributions belong to the family of multivariate normal distributions. The mctfa function fits mixtures of common t-factor analyzers where the component distributions corresponds to multivariate t distributions. Maximum likelihood estimates of the model parameters are obtained using the Expectation–Maximization algorithm.
Keywords for this software
References in zbMATH (referenced in 1 article )
Showing result 1 of 1.
- Morris, Katherine; McNicholas, Paul D.: Clustering, classification, discriminant analysis, and dimension reduction via generalized hyperbolic mixtures (2016)