## refund

I’m lead author of the refund package (CRAN; GitHub). I’ve made contributions to several functions in this package:

• pfr() for penalized scalar-on-function regression
• fpca.sc() for functional principal components analysis
• ccb.fpc() for improved inference for functional principal components analysis
• bayes_fosr() for Bayesian function-on-scalar regression

## tidyfun

Together with Fabian Schiepl, I am an author of the tidyfun package. This package seeks to provide accessible and well-documented software that makes functional data analysis in R easy – specifically data wrangling and exploratory analysis.

The tidyfun webpage includes several illustrative vignettes, and this short overview is a quick place to get started.

## refund.shiny

I worked with Julia Wrobel on the refund.shiny package (CRAN; GitHub; paper).

Through the plot_shiny() function, this package produces interactive graphics for several of the most common functional data analyses:

• Functional principal components analysis
• Multilevel and time-varying functional principal components analysis
• Function-on-scalar regression
• Functional linear concurrent regression

This package is closely aligned with the refund package: analyses are conducted using functions in refund and return objects that can be plotted using refund.shiny::plot_shiny().

## GitHub packages

Code for several projects has been developed on GitHub:

• This website
• vbvs.concurrent, a package for fitting the functional linear concurrent regression model
• gfpca, a package for generalized functional principal components analysis
• Materials for a short course on variable selection in functional regression models