Package: lnmCluster Type: Package Title: Perform Logistic Normal Multinomial Clustering for Microbiome Compositional Data Version: 0.3.1 Authors@R: c( person("Wangshu","Tu",email="wangshu.tu@carleton.ca",role=c("aut","cre")), person("Sanjeena","Dang",email="sanjeena.dang@carleton.ca",role=c("aut")), person("Yuan","Fang",email="yuanf@bu.edu",role=c("aut"))) Maintainer: Wangshu Tu 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) . License: GPL (>= 2) Encoding: UTF-8 RoxygenNote: 7.1.2 Imports: mclust, foreach, MASS, stringr, gtools, pgmm, utils Suggests: knitr, rmarkdown, testthat, mvtnorm VignetteBuilder: knitr Depends: R (>= 3.50) LinkingTo: Rcpp NeedsCompilation: yes Packaged: 2026-07-09 09:18:09 UTC; root Author: Wangshu Tu [aut, cre], Sanjeena Dang [aut], Yuan Fang [aut] Repository: https://cran.r-universe.dev Date/Publication: 2022-07-20 16:50:02 UTC RemoteUrl: https://github.com/cran/lnmCluster RemoteRef: HEAD RemoteSha: d9d56eee60b7ae036c80e22daf23ac001c6de151