Online Program Home
My Program

Abstract Details

Activity Number: 465 - SPEED: Statistical Computing: Methods, Implementation, and Application, Part 1
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract #301715 Presentation
Title: Creation of Two R Shiny Applications to Illustrate and Accompany the growClusters Package
Author(s): Randall Powers* and Terrance Savitsky and Wendy L Martinez
Companies: U.S. Bureau of Labor Statistics and Bureau of Labor Statistics and Bureau of Labor Statistics
Keywords: clustering; R Shiny; partition structure; multivariate data

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.

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

Back to the full JSM 2019 program