fastfrechet is an R package for performing Fréchet regression with univariate distributional responses, including variable selection. The corresponding methodological frameworks have been described in

• Petersen A and Müller H-G (2019), “Fréchet regression for random objects with Euclidean predictors”, Annals of Statistics
• Tucker DC, Wu Y and Müller H-G (2023), “Variable Selection for Global Fréchet Regression”, JASA

The fast implementation and stability selection is based on the algorithm developed in

• Coulter A, Aurora RN, Punjabi N and Gaynanova I (2024), “Fast variable selection for distributional regression with application to continuous glucose monitoring data.” arXiv

To use fastfrechet, you need to install R. To enhance your user experience, you may use some IDE for it (e.g. RStudio).

The development version of fastfrechet is available on GitHub. You can download it with the help of the devtools package in R as follow:

install.packages("devtools")
devtools::install_github("https://github.com/alexandercoulter/fastfrechet", build_vignettes = TRUE)

1. Contributions and suggestions to the software are always welcome. Please consult our contribution guidelines prior to submitting a pull request.
2. Report issues or problems with the software using github’s issue tracker.
3. Contributors must adhere to the Code of Conduct.