Abby Flynt
Bucknell University
7 Papers
Abby Flynt is an academic researcher from Bucknell University. The author has contributed to research in topics: Cluster analysis & Computer science. The author has an hindex of 3, co-authored 7 publications.
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Papers
Diet-related chronic disease in the northeastern United States: a model-based clustering approach
Abby Flynt,Madeleine I. G. Daepp +1 more
TL;DR: Model-based clustering with variable selection offers a new approach to the analysis of socioeconomic, demographic, and environmental data for diet-related chronic disease prediction, and could be applied to larger geographic areas or other countries with comparable data sets.
Comparing finite sequences of discrete events with non-uniform time intervals
Abstract: Algorithms that quantify the similarity between two sequences of data date back to the mid 20th century. Sequence comparison continues to be active area of research in mathematics, statistics, and ...
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Growth Mixture Modeling with Measurement Selection
Abby Flynt,Nema Dean +1 more
TL;DR: In this article, an extension of the growth mixture model that allows for incorporation of stepwise variable selection based on the work done by Maugis et al. was presented, and results presented on a simulation study suggest that the method performs well in correctly selecting the clustering variables and improves on recovery of the cluster structure.
Growth Mixture Modeling with Measurement Selection
Abby Flynt,Nema Dean +1 more
TL;DR: This paper presents an extension of the growth mixture model that allows for incorporation of stepwise variable selection based on the work done by Maugis, Celeux, and Martin-Magniette (2009 and Raftery and Dean (2006), and suggests that the method performs well in correctly selecting the clustering variables and improves on recovery of the cluster structure.
A Survey of Popular R Packages for Cluster Analysis.
Abby Flynt,Nema Dean +1 more
TL;DR: This article reviews the following popular libraries/commands in the R software language for applying different types of cluster analysis: from the stats library, the kmeans, and hclust functions; the mclust library; the poLCA library; and the clustMD library.