CRAN/E | MoMPCA

MoMPCA

Inference and Clustering for Mixture of Multinomial Principal Component Analysis

Installation

About

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) .

Key Metrics

Version 1.0.1
R ≥ 3.6.0
Published 2021-01-21 1194 days ago
Needs compilation? no
License GPL-3
CRAN checks MoMPCA results

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Maintainer

Maintainer

Nicolas Jouvin

nicolas.jouvin@ec-lyon.fr

Authors

Nicolas Jouvin

Material

README
Reference manual
Package source

Vignettes

MoMPCA

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

MoMPCA archive

Depends

R ≥ 3.6.0

Imports

methods
topicmodels
tm
Matrix
slam
magrittr
dplyr
stats
doParallel
foreach

Suggests

testthat ≥ 2.1.0
knitr
markdown
rmarkdown
aricode
ggplot2
tidytext
reshape2