wilcox_R: What the package does (short line)

rmanovab <-
function(x,tr=.2,alpha=.05,grp=0,nboot=599){
#
#   A bootstrap-t for comparing the trimmed means of dependent groups.
#   By default, 20% trimming is used with B=599 bootstrap samples.
#
#   The optional argument grp is used to select a subset of the groups
#   and exclude the rest.
#
#   x can be an n by J matrix or it can have list mode
#
if(is.data.frame(x))x=as.matrix(x)
if(!is.list(x) && !is.matrix(x))stop("Data must be stored in a matrix or in list mode.")
if(is.list(x))mat=matl(x)
#{
#if(sum(grp)==0)grp<-c(1:length(x))
# put the data in an n by J matrix
#mat<-matrix(0,length(x[[1]]),length(grp))
#for (j in 1:length(grp))mat[,j]<-x[[grp[j]]]
#}
if(is.matrix(x)){
if(sum(grp)==0)grp<-c(1:ncol(x))
mat<-x[,grp]
}
mat=elimna(mat)
#if(sum(is.na(mat)>=1))stop("Missing values are not allowed.")
J<-ncol(mat)
connum<-(J^2-J)/2
bvec<-matrix(0,connum,nboot)
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(mat),size=nrow(mat)*nboot,replace=TRUE),nrow=nboot)
xcen<-matrix(0,nrow(mat),ncol(mat))
for (j in 1:J)xcen[,j]<-mat[,j]-mean(mat[,j],tr) #Center data
bvec<-apply(data,1,tsubrmanovab,xcen,tr)
# bvec is vector of nboot  bootstrap test statistics.
icrit<-round((1-alpha)*nboot)
bvec<-sort(bvec)
crit<-bvec[icrit]
test<-rmanova(mat,tr,grp)$test
list(teststat=test,crit=crit)
}