Package: WRI 0.2.3

Alexander Petersen

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:Alexander Petersen [aut, cre], Xi Liu [aut], Chao Zhang [aut], Matthew Coleman [aut]

WRI_0.2.3.tar.gz
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://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • strokeCTdensity - Stroke data: clinical, radiological scalar variables and density curves of the hematoma of 393 stroke patients

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

3.18 score 9 scripts 562 downloads 10 exports 77 dependencies

Last updated from:3cef791c5d. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK201
linux-devel-x86_64OK167
source / vignettesOK241
linux-release-arm64OK169
linux-release-x86_64OK163
wasm-releaseOK167

Exports:confidenceBandsden2Q_qdglobalFtestpartialFtestquan2den_qdsimulate_quantile_curvesWARpwarSimwass_R2wass_regress

Dependencies:backportsbase64encbslibcachemcheckmateclarabelcliclustercolorspacecpp11CVXRdata.tabledigestevaluateexpmfarverfastmapfdapacefontawesomeforeignFormulafsggplot2gluegmpgridExtragtablehighrhighsHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemimemvtnormnnetnumDerivosqppolynompracmaR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRfastrlangrmarkdownrpartrstudioapiS7sassscalesscsslamstringistringrtinytexvctrsviridisLitewithrxfunyamlzigg

Introduction to the WRI Package

Rendered fromWRI-vignette.Rmdusingknitr::rmarkdownon May 29 2026.

Last update: 2020-11-23
Started: 2020-11-23