wilcox_R: What the package does (short line)

iband <-
function(x,alpha=.05,plotit=TRUE,sm=TRUE,SEED=TRUE,nboot=500,grp=c(1:4),
xlab="First Difference",ylab="Delta",crit=NA,print.all=FALSE,plot.op=FALSE){
#
# Apply the shift function when analyzing interactions in a
# 2 by 2 design.
#
# For variables x1, x2, x3 and x4,
# In effect, this function applies a shift function to the distributions
# d1=x1-x2 and d2=x3-x4
#
# grp indicates the groups to be compared. By default grp=c(1,2,3,4)
# meaning that the first four groups are used with the difference between
# the first two compared to the difference between the second two.
# (Rows are  being compared in a 2 by 2 design
# To compare difference between groups 1 and 3 versus 2 and 4 (columns in
#  a 2 by 2 design), set grp=c(1,3,2,4).
#
# print.all=F,
# returns number sig, meaning number of confidence intervals that do not
# contain zero,
# the critical value used as well as the KS test statistics.
# print.all=T reports all confidence intervals, the number of which can
# be large.
#
if(!is.list(x) && !is.matrix(x))stop("store data in list mode or a matrix")
if(SEED)set.seed(2)
if(is.matrix(x))x<-listm(x)
if(length(x)<4)stop("There must be at least 4 groups")
for(j in 1:length(x))x[[j]]=elimna(x[[j]])
if(length(grp)!=4)stop("The argument grp must have 4 values")
x<-x[grp]
n<-c(length(x[[1]]),length(x[[2]]),length(x[[3]]),length(x[[4]]))
# Approximate the critical value
#
vals<-NA
y<-list()
if(is.na(crit)){
print("Approximating critical value. Please wait.")
for(i in 1:nboot){
for(j in 1:4)
y[[j]]<-rnorm(n[j])
temp<-ks.test(outer(y[[1]],y[[2]],FUN="-"),outer(y[[3]],y[[4]],FUN="-"))
vals[i]<-temp[1]$statistic
}
vals<-sort(vals)
ic<-(1-alpha)*nboot
crit<-vals[ic]
}
if(plot.op){
plotit<-F
g2plot(v1,v2)
}
output<-sband(outer(x[[1]],x[[2]],FUN="-"),outer(x[[3]],x[[4]],FUN="-"),
plotit=plotit,crit=crit,flag=FALSE,sm=sm,xlab=xlab,ylab=ylab)
if(!print.all){
numsig<-output$numsig
ks.test.stat<-ks.test(outer(x[[1]],x[[2]],FUN="-"),
outer(x[[3]],x[[4]],FUN="-"))$statistic
output<-matrix(c(numsig,crit,ks.test.stat),ncol=1)
dimnames(output)<-list(c("number sig","critical value","KS test statistics"),
NULL)
}
output
}