TestUSO

This R package provides nonparametric goodness-of-fit tests for uniform stochastic ordering. These tests are proposed by Tang et al. (2017) and Wang et al. (2019). In addition, we provide R programs to reproduce the simulation and the data analysis of Wang et al. (2019) on a GitHub repository: https://github.com/Harrindy/ImprovedGOFforUSO

Installation

library(devtools)
install_github("Harrindy/TestUSO",force=TRUE) 

Illustration:

library(TestUSO)

set.seed(100)
#Generate data:
X=rnorm(30,0,1);Y=rnorm(40,1,1)  

#Calculate the sample ODC Rmn:
EstODC(X,Y,graph=TRUE)    

#Calculate the least star-shaped majorant of the sample ODC Rmn:
LSM(X,Y,graph=TRUE) 

#Conduct the test via the approaches proposed by Tang et al. (2017) and Wang et al. (2019):
GoF4USO(X,Y,alpha=0.05,graph=TRUE) 

[1] "Fixed_cv: critical values using Tang et al. (2017)"
[1] "Reject_USO_fix: reject (1) or not (0) using Tang et al. (2017)"
[1] "AS_cv: critical values using method one of Wang et al. (2019)"
[1] "Reject_USO_AS: reject (1) or not (0) using method one of Wang et al. (2019)"
[1] "RT_cv: critical values using method two of Wang et al. (2019)"
[1] "Reject_USO_RT: reject (1) or not (0) using method two of Wang et al. (2019)"
           Test_statistic Fixed_cv Reject_USO_fix     AS_cv Reject_USO_AS     RT_cv Reject_USO_RT
p=1            0.03968089    0.580              0 0.1028982             0 0.1736021             0
p=2            0.05587717    0.676              0 0.1586878             0 0.2692576             0
p=infinity     0.20701967    1.353              0 0.5865557             0 0.8280787             0

References:

Tang, C., Wang, D., and Tebbs, J. (2017). Nonparametric goodness-of-fit tests for uniform stochastic ordering. Annals of Statistic 48, 2565-2589.

Wang, D., Tang, C., and Tebbs, J. (2019). More powerful goodness-of-fit tests for uniform stochastic ordering. Submitted for publication.

Author:

Dewei Wang (deweiwang@stat.sc.edu)