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:	2.2.0
Imports:	Rcpp (≥ 1.0.5), tidyr, ggplot2, salso
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	xml2, knitr, rmarkdown
Published:	2024-04-18
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_2.2.0.tar.gz
Windows binaries:	r-devel: batchmix_2.2.0.zip, r-release: batchmix_2.2.0.zip, r-oldrel: batchmix_2.2.0.zip
macOS binaries:	r-release (arm64): batchmix_2.2.0.tgz, r-oldrel (arm64): batchmix_2.2.0.tgz, r-release (x86_64): batchmix_2.2.0.tgz, r-oldrel (x86_64): batchmix_2.2.0.tgz
Old sources:	batchmix archive

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