Package: WRI 0.2.0
Xi Liu
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_0.2.0.tar.gz
WRI_0.2.0.tar.gz(r-4.5-noble)WRI_0.2.0.tar.gz(r-4.4-noble)
WRI_0.2.0.tgz(r-4.4-emscripten)WRI_0.2.0.tgz(r-4.3-emscripten)
WRI.pdf |WRI.html✨
WRI/json (API)
NEWS
# Install 'WRI' in R: |
install.packages('WRI', repos = c('https://cran.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 2 years agofrom:16afc2752b. Checks:OK: 1 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 18 2024 |
R-4.5-linux-x86_64 | NOTE | Dec 18 2024 |
Exports:confidenceBandsden2Q_qdglobalFtestpartialFtestquan2den_qdsimulate_quantile_curvesWARpwarSimwass_R2wass_regress
Dependencies:backportsbase64encbitbit64bslibcachemcheckmatecliclueclustercolorspaceCVXRdata.tabledigestECOSolveRevaluateexpmfansifarverfastmapfBasicsfdadensityfdapacefontawesomeforeignFormulafsggplot2gluegmpgridExtragssgtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclelocfitlocpolmagrittrMASSMatrixmemoisemgcvmimemodeestmunsellmvtnormnlmennetnumDerivosqppillarpkgconfigpolynompracmaR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppGSLRcppParallelRcppZigguratRfastrlangrmarkdownRmpfrrmutilrpartrstudioapisassscalesscsspatialstablestablediststatipstringistringrtibbletimeDatetimeSeriestinytexutf8vctrsviridisviridisLitewithrxfunyaml
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 |