Package: miniLNM 0.1.0

miniLNM: Miniature Logistic-Normal Multinomial Models

Logistic-normal Multinomial (LNM) models are common in problems with multivariate count data. This package gives a simple implementation with a 30 line 'Stan' script. This lightweight implementation makes it an easy starting point for other projects, in particular for downstream tasks that require analysis of "compositional" data. It can be applied whenever a multinomial probability parameter is thought to depend linearly on inputs in a transformed, log ratio space. Additional utilities make it easy to inspect, create predictions, and draw samples using the fitted models. More about the LNM can be found in Xia et al. (2013) "A Logistic Normal Multinomial Regression Model for Microbiome Compositional Data Analysis" <doi:10.1111/biom.12079> and Sankaran and Holmes (2023) "Generative Models: An Interdisciplinary Perspective" <doi:10.1146/annurev-statistics-033121-110134>.

Authors:Kris Sankaran [aut, cre]

miniLNM_0.1.0.tar.gz
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miniLNM.pdf |miniLNM.html✨
miniLNM/json (API)

# Install 'miniLNM' in R:
install.packages('miniLNM', repos = c('https://krisrs1128.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/krisrs1128/minilnm/issues

Pkgdown site:https://krisrs1128.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

cpp

4.78 score 1 packages 5 scripts 159 downloads 9 exports 57 dependencies

Last updated 5 months agofrom:57571dad4a. Checks:1 OK, 10 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 11 2025
R-4.5-win-x86_64NOTEFeb 11 2025
R-4.5-mac-x86_64NOTEFeb 11 2025
R-4.5-mac-aarch64NOTEFeb 11 2025
R-4.5-linux-x86_64NOTEFeb 11 2025
R-4.4-win-x86_64NOTEFeb 11 2025
R-4.4-mac-x86_64NOTEFeb 11 2025
R-4.4-mac-aarch64NOTEFeb 11 2025
R-4.3-win-x86_64NOTEFeb 11 2025
R-4.3-mac-x86_64NOTEFeb 11 2025
R-4.3-mac-aarch64NOTEFeb 11 2025

Exports:ansi_aware_handlerbeta_meanbeta_sampleslnmlnm_dataphi_inversepredictprepare_newdatasample

Dependencies:abindbackportsBHcallrcheckmateclicolorspacedescdistributionaldplyrfansifarverformula.toolsgenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivoperator.toolspillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsscalesStanHeaderstensorAtibbletidyselectutf8vctrsviridisLitewithr

Example on Simulated Data

Rendered fromdemo.Rmdusingknitr::rmarkdownon Feb 11 2025.

Last update: 2024-09-07
Started: 2023-12-16