Creation of Two R Shiny Applications to Illustrate and Accompany the growClusters Package

Randall Powers, Terrance Savitsky, and Wendy Martinez

Abstract

GrowClusters is an R package that estimates a clustering or partition structure for multivariate data. Estimation is performed under a penalized optimization derived from Bayesian non-parametric formulations. This is done either under a Dirichlet process (DP) mixing measure or a hierarchical DP (HDP) mixing measure in the limit of the global variance (to zero). The latter set-up allows for a collection of dependent, local partitions. This paper describes the growClusters algorithm, but will focus on the creation of an R Shiny application designed to visually illustrate the operation and functionality of the growClusters package. Examples of the utility and functionality of the R Shiny application will be highlighted.