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: 2.2.1
Imports: Rcpp (≥ 1.0.5), tidyr, ggplot2, salso
LinkingTo: Rcpp, RcppArmadillo
Suggests: xml2, knitr, rmarkdown
Published: 2024-05-21
DOI: 10.32614/CRAN.package.batchmix
Author: Stephen Coleman [aut, cre], Paul Kirk [aut], Chris Wallace [aut]
Maintainer: Stephen Coleman <stcolema at>
License: GPL-3
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README
CRAN checks: batchmix results


Reference manual: batchmix.pdf
Vignettes: Introduction to batchmix


Package source: batchmix_2.2.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): batchmix_2.2.1.tgz, r-oldrel (arm64): batchmix_2.2.1.tgz, r-release (x86_64): batchmix_2.2.1.tgz, r-oldrel (x86_64): batchmix_2.2.1.tgz
Old sources: batchmix archive


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