Interactive graphics for functional data analyses

TL;DR

The paper introduces refund.shiny, an R package that provides interactive visualizations for functional data analysis, making exploratory analysis and communication more efficient and accessible.

Contribution

It presents refund.shiny, a new tool that simplifies creating interactive graphics for functional data analyses, enhancing exploration and understanding.

Findings

Interactive visualizations facilitate exploratory data analysis.

The package reduces time and effort in generating functional data plots.

Visualizations improve communication of results to non-statisticians.

Abstract

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.