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

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