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) for details of the model.
The main functions a user should be aware of are
runMCMCChains, plotLikelihoods,
continueChains and processChains. For an
example of a workflow please see the short vignette.