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Interactive graphics for functional data analyses
Author(s) -
Wrobel Julia,
Park So Young,
Staicu Ana Maria,
Goldsmith Jeff
Publication year - 2016
Publication title -
stat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.61
H-Index - 18
ISSN - 2049-1573
DOI - 10.1002/sta4.109
Subject(s) - computer science , graphics , visualization , exploratory data analysis , exploratory analysis , data visualization , plot (graphics) , intuition , computer graphics , data mining , data science , human–computer interaction , information retrieval , computer graphics (images) , mathematics , philosophy , statistics , epistemology
Although there are established graphics that accompany the most common functional data analyses, generating these graphics for each dataset and analysis can be cumbersome and time‐consuming. Often, the barriers to visualization inhibit useful exploratory data analyses and prevent the development of intuition for a method and its application to a particular dataset. The refund.shiny package was developed to address these issues for several of the most common functional data analyses. After conducting an analysis, the plot_shiny() function is used to generate an interactive visualization environment that contains several distinct graphics, many of which are updated in response to user input. These visualizations reduce the burden of exploratory analyses and can serve as a useful tool for the communication of results to non‐statisticians. Copyright © 2016 John Wiley & Sons, Ltd.