Variable selection for latent class analysis for model-based clustering of multivariate categorical data. The package implements a general framework for selecting the subset of variables with relevant clustering information and discard those that are redundant and/or not informative. The variable selection method is based on the approach of Fop et al. (2017)
|Author||Michael Fop [aut, cre], Thomas Brendan Murphy [ctb]|
|Maintainer||Michael Fop <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on GitHub|
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