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WpProj: Linear p-Wasserstein Projections (original) (raw)

Performs Wasserstein projections from the predictive distributions of any model into the space of predictive distributions of linear models. We utilize L1 penalties to also reduce the complexity of the model space. This package employs the methods as described in Dunipace, Eric and Lorenzo Trippa (2020) <doi:10.48550/arXiv.2012.09999>.

Version: 0.2.3
Depends: R (≥ 4.0)
Imports: approxOT (≥ 1.2), glmnet, oem, Rcpp, rlang, ROI, ROI.plugin.ecos, ROI.plugin.lpsolve, Matrix, rqPen, quantreg, doParallel, foreach, doRNG, dplyr, stats, magrittr, methods, slam, lifecycle
LinkingTo: approxOT (≥ 1.2), BH, Rcpp (≥ 1.0.0), RcppCGAL, RcppEigen, RcppProgress, RSpectra
Suggests: ggplot2, ggsci, ggridges, testthat (≥ 2.1.0), transport, Rmosek, spelling, ECOSolveR
Published: 2025-02-05
DOI: 10.32614/CRAN.package.WpProj
Author: Eric Dunipace ORCID iD [aut, cre], Clemens Schmid ORCID iD [ctb] (ETA progres bar is adapted from their code), Espen Bernton [ctb] ('Hilbert Sort' adapted from their code), Mathieu Gerber [ctb] ('Hilbert Sort' adapted from their code), Pierre Jacob [ctb] ('Hilbert Sort' adapted from their code), Bin Dai [ctb] (W2 projections adapted from their 'OEM' code), Jared Huling ORCID iD [ctb] (W2 projections adapted from their 'OEM' code), Yixuan Qiu [ctb] (W2 projections adapted from their 'OEM' code), Dominic Schuhmacher [ctb] ('Shortsimplex 'optimal transport method adapted from their code), Nicolas Bonneel [ctb] ('Network Simplex' algorithm adapted from their code)
Maintainer: Eric Dunipace
BugReports: https://github.com/ericdunipace/WpProj/issues
License: GPL (== 3.0)
URL: https://github.com/ericdunipace/WpProj
NeedsCompilation: yes
SystemRequirements: C++17
Language: en-US
Materials: README NEWS
CRAN checks: WpProj results

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