Package: WpProj 0.2.3
WpProj: Linear p-Wasserstein Projections
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>.
Authors:
WpProj_0.2.3.tar.gz
WpProj_0.2.3.zip(r-4.5)WpProj_0.2.3.zip(r-4.4)WpProj_0.2.3.zip(r-4.3)
WpProj_0.2.3.tgz(r-4.5-x86_64)WpProj_0.2.3.tgz(r-4.5-arm64)WpProj_0.2.3.tgz(r-4.4-x86_64)WpProj_0.2.3.tgz(r-4.4-arm64)WpProj_0.2.3.tgz(r-4.3-x86_64)WpProj_0.2.3.tgz(r-4.3-arm64)
WpProj_0.2.3.tar.gz(r-4.5-noble)WpProj_0.2.3.tar.gz(r-4.4-noble)
WpProj_0.2.3.tgz(r-4.4-emscripten)WpProj_0.2.3.tgz(r-4.3-emscripten)
WpProj.pdf |WpProj.html✨
WpProj/json (API)
NEWS
| # Install 'WpProj' in R: |
| install.packages('WpProj', repos = c('https://ericdunipace.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ericdunipace/wpproj/issues
Last updated 16 days agofrom:b0a7913682. Checks:11 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 06 2025 |
| R-4.5-win-x86_64 | OK | Feb 06 2025 |
| R-4.5-mac-x86_64 | OK | Feb 06 2025 |
| R-4.5-mac-aarch64 | OK | Feb 06 2025 |
| R-4.5-linux-x86_64 | OK | Feb 06 2025 |
| R-4.4-win-x86_64 | OK | Feb 06 2025 |
| R-4.4-mac-x86_64 | OK | Feb 06 2025 |
| R-4.4-mac-aarch64 | OK | Feb 06 2025 |
| R-4.3-win-x86_64 | OK | Feb 06 2025 |
| R-4.3-mac-x86_64 | OK | Feb 06 2025 |
| R-4.3-mac-aarch64 | OK | Feb 06 2025 |
Exports:binary_program_method_optionscombine.WPR2distCompareHCL0_method_optionsL1_method_optionsL1_penalty_optionsplotridgePlotsimulated_annealing_method_optionsstepwise_method_optionstransport_optionswassersteinWpProjWPR2WPVI
Dependencies:approxOTbackportsbase64encBHbigmemorybigmemory.sribslibcachemcheckmateclicodetoolsdata.tabledigestdoParalleldoRNGdplyrECOSolveRevaluatefansifastmapfontawesomeforeachfsgenericsglmnetgluehighrhqreghrqglashtmltoolsiteratorsjquerylibjsonliteknitrlatticelifecyclelpSolveAPImagrittrMASSMatrixMatrixModelsmemoisemimeoempillarpkgconfigplyrquantregR6rappdirsrbibutilsRcppRcppArmadilloRcppCGALRcppEigenRcppProgressRdpackregistryrlangrmarkdownrngtoolsROIROI.plugin.ecosROI.plugin.lpsolverqPenRSpectrasassshapeslamSparseMsurvivaltibbletidyselecttinytexutf8uuidvctrswithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Options For Use With the Binary Program Method | binary_program_method_options |
| A Function to Combine W_p R ^2 Objects | combine.WPR2 |
| Compares Optimal Transport Distances Between WpProj and Original Models | distCompare |
| Run the Hahn-Carvalho Method | HC |
| Options For Use With the L0 Method | L0_method_options |
| Options For Use With the L1 Method | L1_method_options |
| Recognized L1 Penalties | L1_penalty_options |
| Plot Function for W_p R^2 Objects | plot,WPR2-method |
| Ridge Plots for a Range of Coefficients | ridgePlot |
| Options For Use With the Simulated Annealing Selection Method | simulated_annealing_method_options |
| Options For Use With the Stepwise Selection Method | stepwise_method_options |
| p-Wasserstein Linear Projections | WpProj |
| W_p R^2 Function to Evaluate Performance | WPR2 WPR2,ANY,distcompare-method WPR2,ANY,list-method WPR2,ANY,matrix-method WPR2,ANY,WpProj-method |
| p-Wasserstein Variable Importance | WPVI |
