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:
miniLNM_0.1.0.tar.gz
miniLNM_0.1.0.zip(r-4.5)miniLNM_0.1.0.zip(r-4.4)miniLNM_0.1.0.zip(r-4.3)
miniLNM_0.1.0.tgz(r-4.4-x86_64)miniLNM_0.1.0.tgz(r-4.4-arm64)miniLNM_0.1.0.tgz(r-4.3-x86_64)miniLNM_0.1.0.tgz(r-4.3-arm64)
miniLNM_0.1.0.tar.gz(r-4.5-noble)miniLNM_0.1.0.tar.gz(r-4.4-noble)
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
Last updated 2 months agofrom:57571dad4a. Checks:OK: 2 NOTE: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 13 2024 |
| R-4.5-win-x86_64 | NOTE | Nov 13 2024 |
| R-4.5-linux-x86_64 | OK | Nov 13 2024 |
| R-4.4-win-x86_64 | NOTE | Nov 13 2024 |
| R-4.4-mac-x86_64 | NOTE | Nov 13 2024 |
| R-4.4-mac-aarch64 | NOTE | Nov 13 2024 |
| R-4.3-win-x86_64 | NOTE | Nov 13 2024 |
| R-4.3-mac-x86_64 | NOTE | Nov 13 2024 |
| R-4.3-mac-aarch64 | NOTE | Nov 13 2024 |
Exports:ansi_aware_handlerbeta_meanbeta_sampleslnmlnm_dataphi_inversepredictprepare_newdatasample
Dependencies:abindbackportsBHcallrcheckmateclicolorspacedescdistributionaldplyrfansifarverformula.toolsgenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivoperator.toolspillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsscalesStanHeaderstensorAtibbletidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Pretty Printing | ansi_aware_handler |
| LNM Posterior Mean | beta_mean |
| LNM Posterior Samples | beta_samples |
| Fit a logistic normal multinomial model using R's formula interface. | lnm |
| Simulates data from a Logistic Normal Multinomial Model. | lnm_data |
| S4 Class for a Logistic Normal Multinomial Model | lnm-class |
| Inverse log ratio transformation | phi_inverse |
| LNM Fitted Probabilities | predict,lnm-method |
| Design Matrix for a Model | prepare_newdata |
| LNM Fitted Probabilities | sample,lnm-method |
