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
miniLNM_0.1.0.zip(r-4.7)miniLNM_0.1.0.zip(r-4.6)miniLNM_0.1.0.zip(r-4.5)
miniLNM_0.1.0.tgz(r-4.6-x86_64)miniLNM_0.1.0.tgz(r-4.6-arm64)miniLNM_0.1.0.tgz(r-4.5-x86_64)miniLNM_0.1.0.tgz(r-4.5-arm64)
miniLNM_0.1.0.tar.gz(r-4.7-arm64)miniLNM_0.1.0.tar.gz(r-4.7-x86_64)miniLNM_0.1.0.tar.gz(r-4.6-arm64)miniLNM_0.1.0.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
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/docs site:https://krisrs1128.github.io

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

On CRAN:

Conda:

cpp

4.18 score 1 packages 5 scripts 153 downloads 9 exports 52 dependencies

Last updated from:57571dad4a. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK265
linux-devel-x86_64OK311
source / vignettesOK342
linux-release-arm64OK252
linux-release-x86_64OK245
macos-release-arm64OK252
macos-release-x86_64OK465
macos-oldrel-arm64OK254
macos-oldrel-x86_64OK532
windows-develOK324
windows-releaseOK287
windows-oldrelOK291
wasm-releaseFAIL159

Exports:ansi_aware_handlerbeta_meanbeta_sampleslnmlnm_dataphi_inversepredictprepare_newdatasample

Dependencies:abindbackportsBHcallrcheckmateclicpp11descdistributionaldplyrfansifarverformula.toolsgenericsggplot2gluegridExtragtableinlineisobandlabelinglifecycleloomagrittrmatrixStatsnumDerivoperator.toolspillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsS7scalesStanHeaderstensorAtibbletidyselectutf8vctrsviridisLitewithr

Example on Simulated Data

Rendered fromdemo.Rmdusingknitr::rmarkdownon May 31 2026.

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