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An implementation of logistic normal multinomial (LNM) clustering. It is an extension of LNM mixture model proposed by Fang and Subedi (2020) <doi:10.48550/arXiv.2011.06682>, 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) <doi:10.48550/arXiv.2101.01871> and Tu and Subedi (2022) <doi:10.1002/sam.11555>.
Version: | 0.3.1 |
Depends: | R (≥ 3.50) |
Imports: | mclust, foreach, MASS, stringr, gtools, pgmm, utils |
LinkingTo: | Rcpp |
Suggests: | knitr, rmarkdown, testthat, mvtnorm |
Published: | 2022-07-20 |
DOI: | 10.32614/CRAN.package.lnmCluster |
Author: | Wangshu Tu [aut, cre], Sanjeena Dang [aut], Yuan Fang [aut] |
Maintainer: | Wangshu Tu <wangshu.tu at carleton.ca> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
CRAN checks: | lnmCluster results |
Reference manual: | lnmCluster.pdf |
Vignettes: |
lnmCluster |
Package source: | lnmCluster_0.3.1.tar.gz |
Windows binaries: | r-devel: lnmCluster_0.3.1.zip, r-release: lnmCluster_0.3.1.zip, r-oldrel: lnmCluster_0.3.1.zip |
macOS binaries: | r-release (arm64): lnmCluster_0.3.1.tgz, r-oldrel (arm64): lnmCluster_0.3.1.tgz, r-release (x86_64): lnmCluster_0.3.1.tgz, r-oldrel (x86_64): lnmCluster_0.3.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.