Title: Tidyfun: A new framework for representing and working with function-valued data
Authors: Fabian Scheipl - Ludwig-Maximilians-Universitaet Muenchen (Germany) [presenting]
Jeff Goldsmith - Columbia University (United States)
Abstract: A new R package ``tidyfun'' (https://fabian-s.github.io/tidyfun/) for working with function-valued data is presented which implements a unified interface for dealing with regularly or irregularly observed function-valued data and functional data in basis representation. The package follows the tidyverse design philosophy of R packages and provides idiomatic functions for quickly and easily wrangling and exploring functional data and, specifically, datasets that contain both scalar and functional data or multiple types of functional data, potentially measured over different domains. We discuss the available feature set as well as forthcoming extensions and show some application examples.