Package: deepgmm 0.1.12

deepgmm: Deep Gaussian Mixture Models

Deep Gaussian mixture models as proposed by Viroli and McLachlan (2019) <doi:10.1007/s11222-017-9793-z> 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.

Authors:Cinzia Viroli, Geoffrey J. McLachlan

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deepgmm/json (API)

# Install 'deepgmm' in R:
install.packages('deepgmm', repos = c('https://suren-rathnayake.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/suren-rathnayake/deepgmm/issues

On CRAN:

clusteringdeep-learningmixed-models

3.65 score 9 stars 8 scripts 221 downloads 2 exports 3 dependencies

Last updated 2 years agofrom:cc9ec2436b. Checks:OK: 1 ERROR: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-winERRORNov 02 2024
R-4.5-linuxERRORNov 02 2024
R-4.4-winERRORNov 02 2024
R-4.4-macERRORNov 02 2024
R-4.3-winERRORNov 02 2024
R-4.3-macERRORNov 02 2024

Exports:deepgmmmodel_selection

Dependencies:corpcormclustmvtnorm