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MoMPCA  

Inference and Clustering for Mixture of Multinomial Principal Component Analysis
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]
All associated links for this package
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 21 Dec. 2024.
Previous versions and publish date:
1.0.0 (2020-07-01 11:40), 1.0.1 (2021-01-21 14:10)
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