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lnmCluster  

Perform Logistic Normal Multinomial Clustering for Microbiome Compositional Data
View on CRAN: Click here


Download and install lnmCluster package within the R console
Install from CRAN:
install.packages("lnmCluster")

Install from Github:
library("remotes")
install_github("cran/lnmCluster")

Install by package version:
library("remotes")
install_version("lnmCluster", "0.3.1")



Attach the package and use:
library("lnmCluster")
Maintained by
Wangshu Tu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-07-20
Latest Update: 2022-07-20
Description:
An implementation of logistic normal multinomial (LNM) clustering. It is an extension of LNM mixture model proposed by Fang and Subedi (2020) , and is designed for clustering compositional data. The package includes 3 extended models: LNM Factor Analyzer (LNM-FA), LNM Bicluster Mixture Model (LNM-BMM) and Penalized LNM Factor Analyzer (LNM-FA). There are several advantages of LNM models: 1. LNM provides more flexible covariance structure; 2. Factor analyzer can reduce the number of parameters to estimate; 3. Bicluster can simultaneously cluster subjects and taxa, and provides significant biological insights; 4. Penalty term allows sparse estimation in the covariance matrix. Details for model assumptions and interpretation can be found in papers: Tu and Subedi (2021) and Tu and Subedi (2022) .
How to cite:
Wangshu Tu (2022). lnmCluster: Perform Logistic Normal Multinomial Clustering for Microbiome Compositional Data. R package version 0.3.1, https://cran.r-project.org/web/packages/lnmCluster. Accessed 05 Jun. 2026.
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