Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R

• Main Authors: Angelos Markos, Alfonso Iodice D'Enza, Michel van de Velden
• Format: Article
• Language: English
• Published: Foundation for Open Access Statistics 2019-10-01
• Series: Journal of Statistical Software
• Subjects: dimension reduction; clustering; principal component analysis; multiple correspondence analysis; k-means
• Online Access: https://www.jstatsoft.org/index.php/jss/article/view/2915

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.