title: Interactive graphics for functional data analyses.
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.
authors.affiliation: Department of Biostatistics, Mailman School of Public Health, Columbia University.
authors.forename: Julia
authors.initials: J
authors.lastname: Wrobel
authors.affiliation: Department of Statistics, North Caroline State University.
authors.forename: So Young
authors.initials: SY
authors.lastname: Park
authors.affiliation: Department of Statistics, North Caroline State University.
authors.forename: Ana Maria
authors.initials: AM
authors.lastname: Staicu
authors.affiliation: Department of Biostatistics, Mailman School of Public Health, Columbia University.
authors.forename: Jeff
authors.initials: J
authors.lastname: Goldsmith
keywords: Functional principal component analysis; function-on-scalar regression; longitudinal functional data; multilevel functional data