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.
|
Authors who are presenting talks have a * after their name.