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: | 1.0.1 |
Imports: | Rcpp (≥ 1.0.5), tidyr, ggplot2 |
LinkingTo: | Rcpp, RcppArmadillo, testthat |
Suggests: | xml2, knitr, rmarkdown |
Published: | 2022-06-21 |
Author: | Stephen Coleman [aut, cre], Paul Kirk [aut], Chris Wallace [aut] |
Maintainer: | Stephen Coleman <stephen.coleman at mrc-bsu.cam.ac.uk> |
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: |
Using BatchMixtureModel |
Package source: | batchmix_1.0.1.tar.gz |
Windows binaries: | r-devel: batchmix_1.0.1.zip, r-release: batchmix_1.0.1.zip, r-oldrel: batchmix_1.0.1.zip |
macOS binaries: | r-release (arm64): batchmix_1.0.1.tgz, r-oldrel (arm64): batchmix_1.0.1.tgz, r-release (x86_64): batchmix_1.0.1.tgz, r-oldrel (x86_64): batchmix_1.0.1.tgz |
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