choose.test: Make Recommendations on the Most Powerful Test to Use

In robustrank: Robust Rank-Based Tests

Description

Performs simulations to compare the power of different tests

Usage

choose.test(Xpaired, Ypaired, Xextra = NULL, Yextra = NULL, mc.rep = 1000)

Arguments

Xpaired
Ypaired
Xextra
Yextra
mc.rep

Examples

# There are unpaired observations from both samples
dat=sim.partially.matched(m=20,n.x=40,n.y=5,distr="normal",
    params=c(loc.2=.8,rho=.1,scale.2=1),seed=1)
choose.test(dat$X, dat$Y, dat$Xprime, dat$Yprime)

## There are unpaired observations from only one sample
#dat=sim.partially.matched(m=20,n.x=0,n.y=10,distr="normal",
#    params=c(loc.2=.5,rho=.8,scale.2=1),seed=1)
#choose.test(dat$X, dat$Y, dat$Xprime, dat$Yprime)

robustrank documentation built on July 15, 2020, 5:08 p.m.