deepgmm (0.1.56)

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Deep Gaussian Mixture Models.

Deep Gaussian mixture models as proposed by Viroli and McLachlan (2019) provide a generalization of classical Gaussian mixtures to multiple layers. Each layer contains a set of latent variables that follow a mixture of Gaussian distributions. To avoid overparameterized solutions, dimension reduction is applied at each layer by way of factor models.

Maintainer: Suren Rathnayake
Author(s): Cinzia Viroli, Geoffrey J. McLachlan

License: GPL (>= 3)

Uses: corpcor, mvtnorm, testthat

Released 9 months ago.



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