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Transport theory has seen much success in many fields of statistics and machine learning. We provide a variety of algorithms to compute Wasserstein distance, barycenter, and others. See Peyré and Cuturi (2019) <doi:10.1561/2200000073> for the general exposition to the study of computational optimal transport.
Version: | 0.1.2 |
Depends: | R (≥ 2.10) |
Imports: | CVXR, Rcpp (≥ 1.0.5), Rdpack, lpSolve, stats, utils |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | ggplot2 |
Published: | 2023-04-11 |
DOI: | 10.32614/CRAN.package.T4transport |
Author: | Kisung You [aut, cre] |
Maintainer: | Kisung You <kisungyou at outlook.com> |
License: | MIT + file LICENSE |
NeedsCompilation: | yes |
Materials: | README NEWS |
CRAN checks: | T4transport results |
Reference manual: | T4transport.pdf |
Package source: | T4transport_0.1.2.tar.gz |
Windows binaries: | r-devel: T4transport_0.1.2.zip, r-release: T4transport_0.1.2.zip, r-oldrel: T4transport_0.1.2.zip |
macOS binaries: | r-release (arm64): T4transport_0.1.2.tgz, r-oldrel (arm64): T4transport_0.1.2.tgz, r-release (x86_64): T4transport_0.1.2.tgz, r-oldrel (x86_64): T4transport_0.1.2.tgz |
Old sources: | T4transport archive |
Reverse suggests: | provenance |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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