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 |
| Reference manual: | batchmix.pdf |
| Vignettes: |
Introduction to batchmix |
| Package source: | batchmix_2.1.0.tar.gz |
| Windows binaries: | r-prerel: batchmix_2.1.0.zip, r-release: batchmix_2.1.0.zip, r-oldrel: batchmix_2.1.0.zip |
| macOS binaries: | r-prerel (arm64): batchmix_2.1.0.tgz, r-release (arm64): batchmix_2.1.0.tgz, r-oldrel (arm64): batchmix_2.1.0.tgz, r-prerel (x86_64): batchmix_2.1.0.tgz, r-release (x86_64): batchmix_2.1.0.tgz |
| Old sources: | batchmix archive |
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