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batchmix  

Semi-Supervised Bayesian Mixture Models Incorporating Batch Correction
View on CRAN: Click here


Download and install batchmix package within the R console
Install from CRAN:
install.packages("batchmix")

Install from Github:
library("remotes")
install_github("cran/batchmix")

Install by package version:
library("remotes")
install_version("batchmix", "2.2.2")



Attach the package and use:
library("batchmix")
Maintained by
Stephen Coleman
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-06-21
Latest Update: 2024-05-21
Description:
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.
How to cite:
Stephen Coleman (2022). batchmix: Semi-Supervised Bayesian Mixture Models Incorporating Batch Correction. R package version 2.2.2, https://cran.r-project.org/web/packages/batchmix. Accessed 07 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:20), 1.0.1 (2022-06-21 12:30), 2.0.0 (2023-05-16 17:00), 2.0.1 (2024-02-15 23:40), 2.1.0 (2024-02-25 04:20), 2.2.0 (2024-04-18 17:42), 2.2.1 (2024-05-21 12:40)
Other packages that cited batchmix R package
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Other R packages that batchmix depends, imports, suggests or enhances
Complete documentation for batchmix
Functions, R codes and Examples using the batchmix R package
Some associated functions: batchSemiSupervisedMixtureModel . batchmix-package . calcAllocProb . checkDataGenerationInputs . checkProposalWindows . collectAcceptanceRates . continueChain . continueChains . createSimilarityMat . gammaLogLikelihood . generateBatchData . generateBatchDataLogPoisson . generateBatchDataMVT . generateBatchDataVaryingRepresentation . generateGroupIDsInSimulator . generateInitialLabels . getLikelihood . getSampledBatchScale . getSampledBatchShift . getSampledClusterMeans . invGammaLogLikelihood . invWishartLogLikelihood . plotAcceptanceRates . plotLikelihoods . plotSampledBatchMeans . plotSampledBatchScales . plotSampledClusterMeans . plotSampledParameter . predictClass . predictFromMultipleChains . prepareInitialParameters . processMCMCChain . processMCMCChains . rStickBreakingPrior . runBatchMix . runMCMCChains . sampleMVN . sampleMVT . samplePriorLabels . sampleSemisupervisedMVN . sampleSemisupervisedMVT . wishartLogLikelihood . 
Some associated R codes: RcppExports.R . batchSemiSupervisedMixtureModel.R . batchmix-package.R . calcAllocProb.R . catch-routine-registration.R . checkDataGenerationInputs.R . checkProposalWindows.R . collectAcceptanceRates.R . continueChain.R . continueChains.R . generateBatchData.R . generateBatchDataLogPoisson.R . generateBatchDataMVT.R . generateBatchDataVaryingRepresentation.R . generateGroupIDsInSimulator.R . generateInitialLabels.R . getLikelihood.R . getSampledBatchScale.R . getSampledBatchShift.R . getSampledClusterMeans.R . plotAcceptanceRates.R . plotLikelihoods.R . plotSampledBatchMeans.R . plotSampledBatchScales.R . plotSampledClusterMeans.R . plotSampledParameter.R . predictClass.R . predictFromMultipleChains.R . prepareInitialParameters.R . processMCMCChain.R . processMCMCChains.R . rStickBreakingPrior.R . runBatchMix.R . runMCMCChains.R . samplePriorLabels.R .  Full batchmix package functions and examples
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