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fdWasserstein
View on CRAN: Click
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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]
[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 21 Nov. 2024.
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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