Package: WRI 0.2.3
WRI: Wasserstein Regression and Inference
Implementation of the methodologies described in 1) Alexander Petersen, Xi Liu and Afshin A. Divani (2021) <doi:10.1214/20-aos1971>, including global F tests, partial F tests, intrinsic Wasserstein-infinity bands and Wasserstein density bands, and 2) Chao Zhang, Piotr Kokoszka and Alexander Petersen (2022) <doi:10.1111/jtsa.12590>, including estimation, prediction, and inference of the Wasserstein autoregressive models.
Authors:
WRI_0.2.3.tar.gz
WRI_0.2.3.zip(r-4.7)WRI_0.2.3.zip(r-4.6)WRI_0.2.3.zip(r-4.5)
WRI_0.2.3.tgz(r-4.6-x86_64)WRI_0.2.3.tgz(r-4.6-arm64)WRI_0.2.3.tgz(r-4.5-x86_64)WRI_0.2.3.tgz(r-4.5-arm64)
WRI_0.2.3.tar.gz(r-4.7-arm64)WRI_0.2.3.tar.gz(r-4.7-x86_64)WRI_0.2.3.tar.gz(r-4.6-arm64)WRI_0.2.3.tar.gz(r-4.6-x86_64)
WRI_0.2.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
WRI/json (API)
NEWS
| # Install 'WRI' in R: |
| install.packages('WRI', repos = c('https://alexpete.r-universe.dev', 'https://cloud.r-project.org')) |
- strokeCTdensity - Stroke data: clinical, radiological scalar variables and density curves of the hematoma of 393 stroke patients
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:3cef791c5d. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 190 | ||
| linux-devel-x86_64 | OK | 177 | ||
| source / vignettes | OK | 264 | ||
| linux-release-arm64 | OK | 193 | ||
| linux-release-x86_64 | OK | 208 | ||
| macos-release-arm64 | OK | 166 | ||
| macos-release-x86_64 | OK | 329 | ||
| macos-oldrel-arm64 | OK | 160 | ||
| macos-oldrel-x86_64 | OK | 667 | ||
| windows-devel | OK | 204 | ||
| windows-release | OK | 143 | ||
| windows-oldrel | OK | 118 | ||
| wasm-release | OK | 172 |
Exports:confidenceBandsden2Q_qdglobalFtestpartialFtestquan2den_qdsimulate_quantile_curvesWARpwarSimwass_R2wass_regress
Dependencies:backportsbase64encbslibcachemcheckmateclarabelcliclustercolorspacecpp11CVXRdata.tabledigestevaluateexpmfarverfastmapfdapacefontawesomeforeignFormulafsggplot2gluegmpgridExtragtablehighrhighsHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemimemvtnormnnetnumDerivosqppolynompracmaR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRfastrlangrmarkdownrpartrstudioapiS7sassscalesscsslamstringistringrtinytexvctrsviridisLitewithrxfunyamlzigg
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Confidence Bands for Wasserstein Regression | confidenceBands |
| convert density function to quantile and quantile density function | den2Q_qd |
| global F test for Wasserstein regression | globalFtest |
| partial F test for Wasserstein regression | partialFtest |
| Prediction by WAR(p) models | predict.WARp |
| print the summary of WRI object | print.summary.WRI |
| convert density function to quantile and quantile density function | quan2den_qd |
| Simulate quantile curves | simulate_quantile_curves |
| Stroke data: clinical, radiological scalar variables and density curves of the hematoma of 393 stroke patients | strokeCTdensity |
| Summary Function of Wasserstein Regression Model | summary.WRI |
| WAR(p) models: estimation and forecast | WARp |
| Generate simulation data | warSim |
| Compute Wasserstein Coefficient of Determination | wass_R2 |
| Perform Frechet Regression with the Wasserstein Distance | wass_regress |
