We present the R package clustrd which implements a class of methods that combine dimension reduction and clustering of continuous or categorical data. In particular, for continuous data, the package contains implementations of factorial K-means and reduced K-means; both methods combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means, i-FCB and cluster correspondence analysis, which combine multiple correspondence analysis with K-means. Two examples on real data sets are provided to illustrate the usage of the main functions.

Additional Metadata
Keywords Clustering, Dimension reduction, K-means, Multiple correspondence analysis, Principal component analysis
Persistent URL dx.doi.org/10.18637/jss.v091.i10, hdl.handle.net/1765/121014
Journal Journal of Statistical Software (Online)
Citation
Markos, A, Iodice D’Enza, A, & van de Velden, M. (2019). Beyond tandem analysis: Joint dimension reduction and clustering in R. Journal of Statistical Software (Online), 91(10). doi:10.18637/jss.v091.i10