pb2gen <-
function(x,y,alpha=.05,nboot=2000,est=onestep,SEED=TRUE,pr=FALSE,...){
#
# Compute a bootstrap confidence interval for the
# the difference between any two parameters corresponding to
# independent groups.
# By default, M-estimators are compared.
# Setting est=mean, for example, will result in a percentile
# bootstrap confidence interval for the difference between means.
# Setting est=onestep will compare M-estimators of location.
# The default number of bootstrap samples is nboot=2000
#
x<-x[!is.na(x)] # Remove any missing values in x
y<-y[!is.na(y)] # Remove any missing values in y
if(SEED)set.seed(2) # set seed of random number generator so that
# results can be duplicated.
datax<-matrix(sample(x,size=length(x)*nboot,replace=TRUE),nrow=nboot)
datay<-matrix(sample(y,size=length(y)*nboot,replace=TRUE),nrow=nboot)
bvecx<-apply(datax,1,est,...)
bvecy<-apply(datay,1,est,...)
bvec<-sort(bvecx-bvecy)
low<-round((alpha/2)*nboot)+1
up<-nboot-low
temp<-sum(bvec<0)/nboot+sum(bvec==0)/(2*nboot)
sig.level<-2*(min(temp,1-temp))
se<-var(bvec)
list(est.1=est(x,...),est.2=est(y,...),est.dif=est(x,...)-est(y,...),ci=c(bvec[low],bvec[up]),p.value=sig.level,sq.se=se,n1=length(x),n2=length(y))
}
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