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fdWasserstein  

Application of Optimal Transport to Functional Data Analysis
View on CRAN: Click here


Download and install fdWasserstein package within the R console
Install from CRAN:
install.packages("fdWasserstein")

Install from Github:
library("remotes")
install_github("cran/fdWasserstein")

Install by package version:
library("remotes")
install_version("fdWasserstein", "1.0")



Attach the package and use:
library("fdWasserstein")
Maintained by
Valentina Masarotto
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-02-06
Latest Update: 2024-02-06
Description:
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) ; - compute the Wasserstein barycenter (Frechet mean) as in Masarotto, Panaretos & Zemel (2019) ; - perform analysis of variance testing procedures for functional covariances and tangent space principal component analysis of covariance operators as in Masarotto, Panaretos & Zemel (2022) . - perform a soft-clustering based on the Wasserstein distance where functional data are classified based on their covariance structure as in Masarotto & Masarotto (2023) .
How to cite:
Valentina Masarotto (2024). fdWasserstein: Application of Optimal Transport to Functional Data Analysis. R package version 1.0, https://cran.r-project.org/web/packages/fdWasserstein. Accessed 27 Oct. 2026.
Previous versions and publish date:
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Complete documentation for fdWasserstein
Functions, R codes and Examples using the fdWasserstein R package
Some associated functions: dwasserstein . fdWasserstein-package . gaussBary . phoneme . tangentPCA . wassersteinCluster . wassersteinTest . 
Some associated R codes: gaussBary.R . tangentPCA.R . wassersteinCluster.R . wassersteinTest.R .  Full fdWasserstein package functions and examples
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