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VICatMix is a variational Bayesian finite mixture model
designed for the clustering of categorical data, implemented as an R
package incorporating C++ (via Rcpp and
RcppArmadillo) for faster computation. The package provides
options to include variable selection to enhance its performance on
high-dimensional or noisy data, and to incorporate model averaging and
summarisation over multiple different initialisations for improved
accuracy. The package additionally contains functions to generate sample
clustered binary/categorical data for testing. For more details on the
model, please refer to the arXiv preprint.
To install the VICatMix package, you can use the
devtools package to install directly from GitHub:
install.packages("devtools")
devtools::install_github("j-ackierao/VICatMix")
library(VICatMix)Note VICatMix depends on the Rcpp and
RcppArmadillo packages, which both require an appropriate
C++ compiler.
An example of generating sample binary data for clustering, with ‘true’ cluster labels.
generatedData <- generateSampleDataBin(1000, 4, c(0.1, 0.2, 0.3, 0.4), 100, 0)An example of running one initialisation of VICatMix on
sample data without variable selection:
result <- runVICatMix(generatedData[[1]], 10, 0.01) An example of implementing model averaging over 30 initialisations of
VICatMix on sample data with variable selection:
result <- runVICatMixVarSelAvg(generatedData[[1]], 10, 0.01, inits = 30)These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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