# Semi-Supervised Bayesian Mixture Models Incorporating Batch Correction

## Documentation for package ‘batchmix’ version 2.2.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

batchmix-package | Bayesian Mixture Modelling for Joint Model-Based Clustering/Classification and Batch Correction
batchmix | Bayesian Mixture Modelling for Joint Model-Based Clustering/Classification and Batch Correction
batchmix, | Bayesian Mixture Modelling for Joint Model-Based Clustering/Classification and Batch Correction
BatchMixtureModel | Bayesian Mixture Modelling for Joint Model-Based Clustering/Classification and Batch Correction
batchSemiSupervisedMixtureModel | Batch semisupervised mixture model
calcAllocProb | Calculate allocation probabilities
checkDataGenerationInputs | Check data generation inputs
checkProposalWindows | Check proposal windows
collectAcceptanceRates | Collect acceptance rate
continueChain | Continue chain
continueChains | Continue chains
createSimilarityMat | Create Similarity Matrix
gammaLogLikelihood | Gamma log-likelihood
generateBatchData | Generate batch data
generateBatchDataLogPoisson | Generate batch data
generateBatchDataMVT | Generate batch data from a multivariate t distribution
generateBatchDataVaryingRepresentation | Generate batch data
generateGroupIDsInSimulator | Generate group IDs
generateInitialLabels | Generate initial labels
getLikelihood | Get likelihood
getSampledBatchScale | Get sampled batch shift
getSampledBatchShift | Get sampled batch shift
getSampledClusterMeans | Get sampled cluster means
invGammaLogLikelihood | Inverse gamma log-likelihood
invWishartLogLikelihood | Inverse-Wishart log-likelihood
minVI | Minimium VI
plotAcceptanceRates | Plot acceptance rates
plotLikelihoods | Plot likelihoods
plotSampledBatchMeans | Plot sampled batch means
plotSampledBatchScales | Plot sampled batch scales
plotSampledClusterMeans | Plot sampled cluster means
plotSampledParameter | Plot sampled vector parameter
predictClass | Predict class
predictFromMultipleChains | Predict from multiple MCMC chains
prepareInitialParameters | Prepare initial values
processMCMCChain | Process MCMC chain
processMCMCChains | Process MCMC chains
rStickBreakingPrior | Random Draw From Stick Breaking Prior
runBatchMix | Run Batch Mixture Model
runMCMCChains | Run MCMC Chains
sampleMVN | Sample mixture of multivariate normal distributions with batch effects
sampleMVT | Sample mixture of multivariate t-distributions with batch effects
samplePriorLabels | Sample prior labels
sampleSemisupervisedMVN | Sample semi-supervised MVN Mixture model
sampleSemisupervisedMVT | Sample semi-supervised MVT Mixture model
VI.lb | Minimum VI lower bound
wishartLogLikelihood | Wishart log-likelihood