Scalable Bayesian clustering of categorical datasets. The package implements a hierarchical Dirichlet (Process) mixture of multinomial distributions. It is thus a probabilistic latent class model (LCM) and can be used to reduce the dimensionality of hierarchical data and cluster individuals into latent classes. It can automatically infer an appropriate number of latent classes or find k classes, as defined by the user. The model is based on a paper by Dunson and Xing (2009) <doi:10.1198/jasa.2009.tm08439>, but implements a scalable variational inference algorithm so that it is applicable to large datasets. It is described and tested in the accompanying paper by AhlmannEltze and Yau (2018) <doi:10.1109/DSAA.2018.00068>.
Package details 


Author  Constantin AhlmannEltze [aut, cre] (<https://orcid.org/000000023762068X>), Christopher Yau [ths] (<https://orcid.org/0000000176158523>) 
Maintainer  Constantin AhlmannEltze <artjom31415@googlemail.com> 
License  GPL3 
Version  0.3.0 
URL  https://github.com/constae/mixdir 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

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