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Activity Number: 158 - SPEED: Statistical Methods, Computing, and Applications Part 2
Type: Contributed
Date/Time: Monday, August 8, 2022 : 10:30 AM to 11:15 AM
Sponsor: Section on Statistical Computing
Abstract #323747
Title: The growclusters Package for R
Author(s): Randall Powers* and Wendy Martinez and Terrance D Savitsky
Companies: Bureau of Labor Statistics and Bureau of Labor Statistics and U.S. Bureau of Labor Statistics
Keywords: clustering; R Shiny; unsupervised learning; k-means
Abstract:

The growclusters package for R implements an enhanced version of k-means clustering that allows discovery of local clusterings or partitions for a collection of data sets that each draw their cluster means from a single, global partition. The package contains functions to estimate a partition structure for multivariate data. Estimation is performed under a penalized optimization derived from Bayesian non-parametric formulations. This paper describes some of the functions and capabilities of the growclusters package, including the creation of R Shiny applications designed to visually illustrate the operation and functionality of the growclusters package.


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