wilcox_R: What the package does (short line)

bd1way <-
function(x,est=tmean,nboot=599,alpha=.05,SEED=TRUE,misran=FALSE,na.rm=NULL,pr=TRUE,...){
#
#   Test the hypothesis of equal measures of location for J
#   dependent groups using a
#   percentile bootstrap method.
#   By default, a one-step M-estimator is used.
#   For example, bd1way(x,mean) would compare means
#
#   Data are assumed to be stored  in list mode or an n by J matrix.
#   misran=F means missing values do not occur at random, case wise deletion is used.
#   misran=T, all values will be used assuming missing values occur at random
#   OR set na.rm=F to use all of the data. na.rm=F means misran=T will be used.
#   In effect, specifying na.rm=T, for example, the argument misran is ignored.
#
if(!is.list(x) && !is.matrix(x))stop("Data must be stored in list mode or in an n by J matrix.")
if(pr)print('As of Oct, 2015, the default measure of location is a trimmed mean, not the one-step M-estimator')
if(is.list(x)){
m<-matrix(0,length(x[[1]]),length(x))
for (j in 1:length(x))m[,j]<-x[[j]]
}
if(is.matrix(x))m<-x
if(!is.null(na.rm))misran=!na.rm
if(!misran)m=elimna(m)
xcen<-m
locval=apply(m,2,est,na.rm=TRUE,...)
for (j in 1:ncol(m))xcen[,j]<-m[,j]-est(m[,j],na.rm=misran,...)
if(SEED)set.seed(2) # set seed of random number generator so that
#             results can be duplicated.
print("Taking bootstrap samples. Please wait.")
data<-matrix(sample(nrow(m),size=nrow(m)*nboot,replace=TRUE),nrow=nboot)
bvec<-vector("numeric")
bvec<-apply(data,1,bd1way1,xcen,est,misran=misran,...)
# A vector of  nboot test statistics.
icrit<-floor((1-alpha)*nboot+.5)
testv<-vector("numeric")
for (j in 1:ncol(m))testv[j]<-est(m[,j],na.rm=misran,...)
test<-(length(testv)-1)*var(testv)
pv=mean((test<bvec))
list(test=test,estimates=locval,p.value=pv)
}