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MoMPCA
View on CRAN: Click
here
Download and install MoMPCA package within the R console
Install from CRAN:
install.packages("MoMPCA")
Install from Github:
library("remotes")
install_github("cran/MoMPCA")
Install by package version:
library("remotes")
install_version("MoMPCA", "1.0.1")
Attach the package and use:
library("MoMPCA")
Maintained by
Nicolas Jouvin
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
First Published: 2020-07-01
Latest Update: 2023-08-19
Description:
Cluster any count data matrix with a fixed number of variables, such as document/term matrices. It integrates the dimension reduction aspect of topic models in the mixture models framework. Inference is done by means of a greedy Classification Variational Expectation Maximisation (C-VEM) algorithm. An Integrated Classication Likelihood (ICL) model selection is designed for selecting the latent dimension (number of topics) and the number of clusters. For more details, see the article of Jouvin et. al. (2020) .
How to cite:
Nicolas Jouvin (2020). MoMPCA: Inference and Clustering for Mixture of Multinomial Principal
Component Analysis. R package version 1.0.1, https://cran.r-project.org/web/packages/MoMPCA. Accessed 31 Mar. 2025.
Other packages that cited MoMPCA R package
View MoMPCA citation profile
Other R packages that MoMPCA depends,
imports, suggests or enhances
Functions, R codes and Examples using
the MoMPCA R package
Some associated functions: BBCmsg . DTMtoSparse . MoMPCA . benchmarks-functions . initializeBeta . initialize_Y . mmpcaClust-class . mmpcaClustcontrol-class . mmpca_clust . mmpca_clust_modelselect . pipe . plot-mmpcaClust-missing-method . plot_bound . plot_topics . simulate_BBC .
Some associated R codes: BBCVEM.R . MoMPCA.R . benchmarks.R . data.R . init_functions.R . mmpcaClust_class.R . mmpcaClustcontrol_class.R . mmpca_clust.R . mmpca_clust_modelselection.R . plot.R . simulate_BBC.R . utility_functions.R . utils-pipe.R . Full MoMPCA package functions and examples
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