fdWasserstein: Application of Optimal Transport to Functional Data Analysis
These functions were developed to support statistical analysis on functional covariance operators.
The package contains functions to:
- compute 2-Wasserstein distances between Gaussian Processes as in
Masarotto, Panaretos & Zemel (2019) <doi:10.1007/s13171-018-0130-1>;
- compute the Wasserstein barycenter (Frechet mean) as in Masarotto,
Panaretos & Zemel (2019) <doi:10.1007/s13171-018-0130-1>;
- perform analysis of variance testing procedures for functional
covariances and tangent space principal component analysis of
covariance operators as in Masarotto, Panaretos & Zemel (2022)
<doi:10.48550/arXiv.2212.04797>.
- perform a soft-clustering based on the Wasserstein distance where
functional data are classified based on their covariance structure
as in Masarotto & Masarotto (2023) <doi:10.1111/sjos.12692>.
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=fdWasserstein
to link to this page.