Nothing
yuenbt <- function(formula, data, tr = 0.2, nboot = 599, side = TRUE, ...){
if (missing(data)) {
mf <- model.frame(formula)
} else {
mf <- model.frame(formula, data)
}
cl <- match.call()
xy <- split(model.extract(mf, "response"), mf[,2])
faclevels <- names(xy)
x <- xy[[1]]
y <- xy[[2]]
alpha<-.05
nullval<-0
pr<-TRUE
plotit<-FALSE
op<-1
side<-as.logical(side)
p.value<-NA
yuenbt<-vector(mode="numeric",length=2)
x<-x[!is.na(x)] # Remove missing values in x
y<-y[!is.na(y)] # Remove missing values in y
xcen<-x-mean(x,tr)
ycen<-y-mean(y,tr)
test<-(mean(x,tr)-mean(y,tr))/sqrt(trimse(x,tr=tr)^2+trimse(y,tr=tr)^2)
datax<-matrix(sample(xcen,size=length(x)*nboot,replace=TRUE),nrow=nboot)
datay<-matrix(sample(ycen,size=length(y)*nboot,replace=TRUE),nrow=nboot)
top<-apply(datax,1,mean,tr)-apply(datay,1,mean,tr)
botx<-apply(datax,1,trimse,tr)
boty<-apply(datay,1,trimse,tr)
tval<-top/sqrt(botx^2+boty^2)
if(side)tval<-abs(tval)
tval<-sort(tval)
icrit<-floor((1-alpha)*nboot+.5)
ibot<-floor(alpha*nboot/2+.5)
itop<-floor((1-alpha/2)*nboot+.5)
se<-sqrt((trimse(x,tr))^2+(trimse(y,tr))^2)
yuenbt[1]<-mean(x,tr)-mean(y,tr)-tval[itop]*se
yuenbt[2]<-mean(x,tr)-mean(y,tr)-tval[ibot]*se
if(side){
yuenbt[1]<-mean(x,tr)-mean(y,tr)-tval[icrit]*se
yuenbt[2]<-mean(x,tr)-mean(y,tr)+tval[icrit]*se
p.value<-(sum(abs(test)<=abs(tval)))/nboot
}
mdiff <- mean(x,tr)-mean(y,tr)
result <- list(test = test, conf.int = yuenbt, p.value = p.value, df = NA, diff = mdiff, call = cl)
class(result) <- "yuen"
result
}
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