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Activity Number:
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531
- SPEED: Statistical Computing: Methods, Implementation, and Application, Part 2
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Type:
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Contributed
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Date/Time:
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Wednesday, July 31, 2019 : 11:35 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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Abstract #307939
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Title:
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Creation of Two R Shiny Applications to Illustrate and Accompany the growClusters Package
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Author(s):
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Randall Powers* and Terrance Savitsky and Wendy L Martinez
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Companies:
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U.S. Bureau of Labor Statistics and Bureau of Labor Statistics and Bureau of Labor Statistics
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Keywords:
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clustering;
R Shiny;
partition structure;
multivariate data
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Abstract:
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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.
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Authors who are presenting talks have a * after their name.
