Man pages for WRI
Wasserstein Regression and Inference
| confidenceBands | Confidence Bands for Wasserstein Regression |
| den2Q_qd | convert density function to quantile and quantile density... |
| Exp_Map_Barycenter_Method | Numerical implementation of the Exponential map |
| Exp_Map_Barycenter_Method_pw | Numerical implementation of the pointwise Exponential map |
| getInnovation | Calculating innovations in WAR(p) models |
| globalFstat | An internal function used in bootstrap global F test |
| globalFtest | global F test for Wasserstein regression |
| partialFtest | partial F test for Wasserstein regression |
| predict.WARp | Prediction by WAR(p) models |
| print.summary.WRI | print the summary of WRI object |
| quadraticQ | An internal function to do quadratic program in order to make... |
| quan2den_qd | convert density function to quantile and quantile density... |
| Sample_ACV | Function for calculating sample autocovariance |
| simulate_quantile_curves | Simulate quantile curves |
| strokeCTdensity | Stroke data: clinical, radiological scalar variables and... |
| summary.WRI | Summary Function of Wasserstein Regression Model |
| WARp | WAR(p) models: estimation and forecast |
| WARp_acvfs | Function for calculating sample Wasserstein autocovariance... |
| WARp_forecast_tangent | Forecast using WAR(p) models |
| warSim | Generate simulation data |
| wass_R2 | Compute Wasserstein Coefficient of Determination |
| wass_regress | Perform Frechet Regression with the Wasserstein Distance |
