batchmix: Semi-Supervised Bayesian Mixture Models Incorporating Batch Correction

Semi-supervised and unsupervised Bayesian mixture models that simultaneously infer the cluster/class structure and a batch correction. Densities available are the multivariate normal and the multivariate t. The model sampler is implemented in C++. This package is aimed at analysis of low-dimensional data generated across several batches. See Coleman et al. (2022) <doi:10.1101/2022.01.14.476352> for details of the model.

Version: 2.1.0
Imports: Rcpp (≥ 1.0.5), tidyr, ggplot2
LinkingTo: Rcpp, RcppArmadillo, testthat
Suggests: xml2, knitr, rmarkdown
Published: 2024-02-25
Author: Stephen Coleman [aut, cre], Paul Kirk [aut], Chris Wallace [aut]
Maintainer: Stephen Coleman <stcolema at tcd.ie>
BugReports: https://github.com/stcolema/batchmix/issues
License: GPL-3
URL: https://github.com/stcolema/batchmix
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README
CRAN checks: batchmix results

Documentation:

Reference manual: batchmix.pdf
Vignettes: Introduction to batchmix

Downloads:

Package source: batchmix_2.1.0.tar.gz
Windows binaries: r-devel: batchmix_2.1.0.zip, r-release: batchmix_2.1.0.zip, r-oldrel: batchmix_2.1.0.zip
macOS binaries: r-release (arm64): batchmix_2.1.0.tgz, r-oldrel (arm64): batchmix_2.1.0.tgz, r-release (x86_64): batchmix_2.1.0.tgz
Old sources: batchmix archive

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